Can supervise: YES
Garshasbi, S, Mohammadi, Y, Graf, S, Garshasbi, S & Shen, J 2019, 'Optimal learning group formation: A multi-objective heuristic search strategy for enhancing inter-group homogeneity and intra-group heterogeneity', EXPERT SYSTEMS WITH APPLICATIONS, vol. 118, pp. 506-521.View/Download from: Publisher's site
Wu, Q, Shen, J, Yong, B, Wu, J, Li, F, Wang, J & Zhou, Q 2019, 'Smart fog based workflow for traffic control networks', FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, vol. 97, pp. 825-835.View/Download from: Publisher's site
Chen, H, Guo, W, Shen, J, Wang, L & Song, J 2018, 'Structural Principles Analysis of Host-Pathogen Protein-Protein Interactions: A Structural Bioinformatics Survey', IEEE Access, vol. 6, pp. 11760-11771.View/Download from: UTS OPUS or Publisher's site
© 2013 IEEE. Computational-intelligence methods in bioinformatics and systems biology show promising potential for leveraging abundant, large-scale molecular data. These methods can facilitate analysis and prediction of the principles of biological systems through the construction of statistical and visualized models. Specifically, structural data from exogenous and endogenous protein-protein interactions are of vital significance in this context, encompassing primarily 3-D structural information for a cohort of macromolecules underpinning the biological system. In this paper, we surveyed the main methodologies and algorithms for the reconstruction and modeling of the structural-interaction networks (SINs) of host-pathogen protein-protein interactions (HPPPIs), regarding how the protein domains interact with each other to constitute a SIN. Surveying the pattern and the organization of the SIN delivers a state-of-The-Art view of HPPPIs and illustrates prospective future research directions. In addition to the binary PPI network, we distilled the relevant data sources into several branching research areas and further expanded the discussions into computational-intelligence methods according to the algorithms applied, including machine learning statistical models, to shed light on effective method design. In particular, atomic resolution level investigations can reveal novel insights into the underlying principles of the organization and the complexity of HPPPIs networks. Combining data analytics and machine-learning technologies, we anticipate that our systematic overview will serve as a useful guide for interested researchers to carry out related studies on this exciting and challenging research topic in system biology.
Dong, G, Li, W, Shen, J, Wang, Y, Fu, X & Guo, WW 2018, 'Solving traveling salesman problems with ant colony optimization algorithms in sequential and parallel computing environments: A normalized comparison', International Journal of Machine Learning and Computing, vol. 8, no. 2, pp. 98-103.View/Download from: UTS OPUS or Publisher's site
© 2018, International Association of Computer Science and Information Technology. In recent years some comparative studies have explored the use of parallel ant colony optimization (ACO) algorithms over the traditionally sequential ACOs to solve the traveling salesman problem (TSP). However, these studies did not take a systematical approach to assess the performance of both algorithms on a comparable ground. In this paper, we aim to make a comparison of both the quality of the solutions and the running time as a result of the application of a sequential ACO and a parallel ACO to Eil51, Eil76 and KroA100 on a normalized and thus, comparable ground. Our study reaffirmed that the parallel algorithm is superior in computing efficiency over the sequential algorithm, particularly for larger TSPs. We also found that such a comparison could be meaningless if the size of the TSPs keeps increasing. We revealed that the worst solution among 10 repeated runs obtained from the parallel ACO was still better than the best solution among 10 repeated runs obtained from the sequential ACO, though both did not reach the global optimal solution within 300 iterations. The proposed parallel ACO has a very high consistency because at least one best solution was found within an error of 0.5% to the global optimal solution in every three repeats for all three cases.
Li, R, Rose, G, Chen, H & Shen, J 2018, 'Effective long-term travel time prediction with fuzzy rules for tollway', NEURAL COMPUTING & APPLICATIONS, vol. 30, no. 9, pp. 2921-2933.View/Download from: Publisher's site
Shi, J, Luo, J, Dong, F, Jin, J & Shen, J 2018, 'Fast multi-resource allocation with patterns in large scale cloud data center', JOURNAL OF COMPUTATIONAL SCIENCE, vol. 26, pp. 389-401.View/Download from: Publisher's site
Sun, G, Cui, T, Yong, J, Shen, J & Chen, S 2018, 'MLaaS: A Cloud-Based System for Delivering Adaptive Micro Learning in Mobile MOOC Learning', IEEE TRANSACTIONS ON SERVICES COMPUTING, vol. 11, no. 2, pp. 292-305.View/Download from: Publisher's site
Wang, L & Shen, J 2018, 'Data-Intensive Service Provision Based on Particle Swarm Optimization', INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, vol. 11, no. 1, pp. 330-339.View/Download from: UTS OPUS
Yong, B, Shen, J, Shen, Z, Chen, H, Wang, X & Zhou, Q 2018, 'GVM based intuitive simulation web application for collision detection', Neurocomputing, vol. 279, pp. 63-73.View/Download from: Publisher's site
© 2017 Elsevier B.V. Computer simulation, which has been proved to be an effective approach to problem solving, is nowadays widely used in modern science. However, it requires a lot of computing resources, which are difficult for general users to acquire. In this paper, we design a Web based system to implement on-line simulation system for ordinary users. As a useful example, the simulation of one type of collision detection model is presented in this paper. Moreover, the software application of simulation is offered as a service on Web. Meanwhile, the incorporation of general vector machine (GVM, a type of neural network) to intelligently predict the relationship between simulation parameters and computation resources is presented, which could further provide more information for system monitoring and scheduling. The system has demonstrated efficiency and intuitiveness for users of this type of applications.
Zhou, Q, Chen, C, Zhang, G, Chen, H, Chen, D, Yan, Y, Shen, J & Zhou, R 2018, 'Real-time management of groundwater resources based on wireless sensors networks', Journal of Sensor and Actuator Networks, vol. 7, no. 1.View/Download from: UTS OPUS or Publisher's site
© 2018 by the authors Groundwater plays a vital role in the arid inland river basins, in which the groundwater management is critical to the sustainable development of area economy and ecology. Traditional sustainable management approaches are to analyze different scenarios subject to assumptions or to construct simulation–optimization models to obtain optimal strategy. However, groundwater system is time-varying due to exogenous inputs. In this sense, the groundwater management based on static data is relatively outdated. As part of the Heihe River Basin (HRB), which is a typical arid river basin in Northwestern China, the Daman irrigation district was selected as the study area in this paper. First, a simulation–optimization model was constructed to optimize the pumping rates of the study area according to the groundwater level constraints. Three different groundwater level constraints were assigned to explore sustainable strategies for groundwater resources. The results indicated that the simulation–optimization model was capable of identifying the optimal pumping yields and satisfy the given constraints. Second, the simulation–optimization model was integrated with wireless sensors network (WSN) technology to provide real-time features for the management. The results showed time-varying feature for the groundwater management, which was capable of updating observations, constraints, and decision variables in real time. Furthermore, a web-based platform was developed to facilitate the decision-making process. This study combined simulation and optimization model with WSN techniques and meanwhile attempted to real-time monitor and manage the scarce groundwater resource, which could be used to support the decision-making related to sustainable management.
Zhou, Q, Sun, H, Zhou, R, Sun, G, Shen, J & Li, KC 2018, 'A collaborative and open solution for large-scale online learning', Computer Applications in Engineering Education, vol. 26, no. 6, pp. 2266-2281.View/Download from: UTS OPUS or Publisher's site
© 2018 Wiley Periodicals, Inc. Collaborative Open Online Courses (COOC), designed as the enhanced variance of Massive Open Online Courses (MOOC), inherently combines the advantages of high-quality online resources and face-to-face classroom teaching. It stimulates the collaboration and improvement of courses between educators and learners, by realizing the innovation for dynamic and real-time education process, fostering professional skill acquisition and development as well. In this paper, we propose the novel concept and architectural design of COOC that provides the online course, courseware, and online experimental platform, built on top of third party's open source platforms. The preparation of courses is based on GitHub that facilitates multipoint-to-multipoint online courses and concurrent compilation of textbook based on GitBook, by providing open source textbooks and rapid updates as well as remote operations through online experimental platforms. The major differences between MOOC and COOC include decentralized platform and adoption of concepts through crowdsourcing, where instructors, professionals, and learners are able to set up and modify the courses independently and concurrently, empowering the course's construction based on the collaborative, open and shared textbooks, and online experimental platform. Users, including both teachers and learners, are also able to browse, download, and make use of courses in this platform. With embedded intellectual property and quality control mechanisms, such as Creative Commons (CC) licenses, COOC platform can generate and offer high-quality courses and textbooks of emerging knowledge rapidly through consistent updates by professionals, students, and elites in related domains. The proposed design has been tested at trial Chinese universities and initial feedback from instructors and students are very positive. Insights on techniques and related information are provided, to best adapt to any vocational education...
Sun, G, Cui, T, Beydoun, G, Chen, S, Dong, F, Xu, D & Shen, J 2017, 'Towards massive data and sparse data in adaptive micro open educational resource recommendation: A study on semantic knowledge base construction and cold start problem', Sustainability, vol. 9, no. 6, pp. 1-21.View/Download from: UTS OPUS or Publisher's site
© 2017 by the authors. Micro Learning through open educational resources (OERs) is becoming increasingly popular. However, adaptive micro learning support remains inadequate by current OER platforms. To address this, our smart system, Micro Learning as a Service (MLaaS), aims to deliver personalized OER with micro learning to satisfy their real-time needs. In this paper, we focus on constructing a knowledge base to support the decision-making process of MLaaS. MLaas is built using a top-down approach. A conceptual graph-based ontology construction is first developed. An educational data mining and learning analytic strategy is then proposed for the data level. The learning resource adaptation still requires learners' historical information. To compensate for the absence of this information initially (aka 'cold start'), we set up a predictive ontology-based mechanism. As the first resource is delivered to the beginning of a learner's learning journey, the micro OER recommendation is also optimized using a tailored heuristic.
Sun, G, Cui, T, Guo, W, Chen, S & Shen, J 2017, 'A Framework of MLaaS for Facilitating Adaptive Micro Learning through Open Education Resources in Mobile Environment', INTERNATIONAL JOURNAL OF WEB SERVICES RESEARCH, vol. 14, no. 4, pp. 50-74.View/Download from: Publisher's site
Topi, H, Karsten, H, Brown, SA, Carvalho, JA, Donnellan, B, Shen, J, Tan, BCY & Thouin, MF 2017, 'MSIS 2016 global competency model for graduate degree programs in information systems', Communications of the Association for Information Systems, vol. 40, no. 1, p. MSIS-i-MSIS-107.
Yong, B, Shen, J, Sun, H, Chen, H & Zhou, Q 2017, 'Parallel GPU-based collision detection of irregular vessel wall for massive particles', CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, vol. 20, no. 3, pp. 2591-2603.View/Download from: Publisher's site
Al-Isma'ili, S, Li, M, Shen, J & He, Q 2016, 'Cloud computing adoption decision modelling for SMEs: a conjoint analysis', INTERNATIONAL JOURNAL OF WEB AND GRID SERVICES, vol. 12, no. 3, pp. 296-327.View/Download from: Publisher's site
Sun, G & Shen, J 2016, 'Towards organizing smart collaboration and enhancing teamwork performance: a GA-supported system oriented to mobile learning through cloud-based online course', INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, vol. 7, no. 3, pp. 391-409.View/Download from: Publisher's site
Wang, L & Shen, J 2016, 'Multi-Phase Ant Colony System for Multi-Party Data-Intensive Service Provision', IEEE TRANSACTIONS ON SERVICES COMPUTING, vol. 9, no. 2, pp. 264-276.View/Download from: Publisher's site
Wang, L, Shen, J, Zhou, Q, Shang, Z, Chen, H & Zhao, H 2016, 'An Evaluation of the Dynamics of Diluted Neural Network', INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, vol. 9, no. 6, pp. 1191-1199.View/Download from: Publisher's site
Zhou, Q, Wu, J, Wu, T, Shen, J & Zhou, R 2016, 'Learning Network Storage Curriculum With Experimental Case Based on Embedded Systems', COMPUTER APPLICATIONS IN ENGINEERING EDUCATION, vol. 24, no. 2, pp. 186-194.View/Download from: Publisher's site
Wang, L, Shen, J & Luo, J 2015, 'Facilitating an ant colony algorithm for multi-objective data-intensive service provision', JOURNAL OF COMPUTER AND SYSTEM SCIENCES, vol. 81, no. 4, pp. 734-746.View/Download from: Publisher's site
Shen, J, Beydoun, G, Low, G & Wang, L 2014, 'Aligning ontology-based development with service oriented systems', FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF GRID COMPUTING AND ESCIENCE, vol. 32, pp. 263-273.View/Download from: UTS OPUS or Publisher's site
Sun, G & Shen, J 2014, 'Facilitating Social Collaboration in Mobile Cloud-Based Learning: A Teamwork as a Service (TaaS) Approach', IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES, vol. 7, no. 3, pp. 207-220.View/Download from: Publisher's site
Ismail, A, Yan, J & Shen, J 2013, 'Incremental service level agreements violation handling with time impact analysis', JOURNAL OF SYSTEMS AND SOFTWARE, vol. 86, no. 6, pp. 1530-1544.View/Download from: Publisher's site
Sombattheera, C & Shen, J 2013, 'Towards optimal service composition upon QoS in agent cooperation', International Journal of Computational Science and Engineering, vol. 8, no. 2, pp. 119-132.View/Download from: Publisher's site
It is quite common in tourism industry that a tourist would love to gain the most wonderful experience from visiting multiple places in one trip. This is a service composition problem and is difficult to manage because of several reasons. We address this problem by proposing an agent-based service composition framework to allocate to the tourist an optimal composite service. We take into account a number of factors including: 1) all the places of interest must be visited; 2) the preference on visiting places must be obeyed; 3) the total price is within the budget; 4) the time constraint must be obeyed; 5) the payoffs for service providers are worthwhile and fair. We propose a bottom-up approach to allocate the optimal service composition where intelligent agents are deployed to provide flexibility and efficiency to the system. As a result, the system is more independent and every party is better off. Copyright © 2013 Inderscience Enterprises Ltd.
Sun, Z & Shen, J 2013, 'A high performance peer to cloud and peer model augmented with hierarchical secure communications', JOURNAL OF SYSTEMS AND SOFTWARE, vol. 86, no. 7, pp. 1790-1796.View/Download from: Publisher's site
Al-Hmouz, A, Shen, J, Al-Hmouz, R & Yan, J 2012, 'Modeling and Simulation of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for Mobile Learning', IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES, vol. 5, no. 3, pp. 226-237.View/Download from: Publisher's site
Shen, J, Kim, SD & Venkatasubramanian, N 2012, 'Editorial notes', Computer Systems Science and Engineering, vol. 27, no. 2, p. 87.
Shen, J, Kim, SD & Venkatasubramanian, N 2012, 'Guest editorial notes for selected papers from SOCA 2010', Service Oriented Computing and Applications, vol. 6, no. 2, pp. 81-82.View/Download from: Publisher's site
Shen, J, Kim, SD & Venkatasubramanian, N 2012, 'SPECIAL ISSUE: SERVICE ORIENTED COMPUTING AND APPLICATIONS', COMPUTER SYSTEMS SCIENCE AND ENGINEERING, vol. 27, no. 2, pp. 87-87.
Zhang, Y, Yu, P & Shen, J 2012, 'The benefits of introducing electronic health records in residential aged care facilities: A multiple case study', INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, vol. 81, no. 10, pp. 690-704.View/Download from: Publisher's site
Ahmed, W, Aslam, MA, Lopez-Lorca, AA, Shen, J, Beydoun, G & Richards, D 2011, 'Using Ontologies to Synchronize Change in Relational Database Systems', JOURNAL OF RESEARCH AND PRACTICE IN INFORMATION TECHNOLOGY, vol. 43, no. 2, pp. 89-107.View/Download from: UTS OPUS
Ismail, A, Yan, J & Shen, J 2010, 'An offer generation approach to SLA negotiation support in service oriented computing', Service Oriented Computing and Applications, vol. 4, no. 4, pp. 277-289.View/Download from: Publisher's site
Service level agreement (SLA) plays an important role in realizing service-oriented application. With SLA negotiation mechanism, both parties namely the requester and the provider can exchange information of SLA parameters towards establishing an agreement. In this paper, we study the roles of both parties and focus on how service providers generate offers upon receiving the requests from service requesters. From the provider's perspective, the provider has to decide the right values to offer based on its current resource availability while aiming to satisfy the requester requirements (if possible). Therefore, in this paper, we propose an approach to addressing offer generation, including the architecture, the information modeling and the generation algorithm. We then provide a case study to illustrate the usefulness of the approach, followed by an analysis to justify the effectiveness of the approach. © 2010 Springer-Verlag London Limited.
Shen, J & Yuan, S 2009, 'Adaptive e-services selection in P2P-based workflow with multiple property specifications', Studies in Computational Intelligence, vol. 172, pp. 153-167.View/Download from: Publisher's site
P2P (Peer-to-Peer) based service computing has emerged as an important new field in the distributed computing arena. It focuses on intensive service sharing, innovative applications and compositions, and in some cases, high performance orientation. However, the main challenge for P2P-based service composition process is how to intelligently mining and selection the most appropriate peers to execute the service application in complex and dynamic situations. Traditional methodologies are still very inadequate to effectively and autonomously conduct the service mining and selection in a real-time environment, as they seldom consider and focus on dealing with complex situations, such as simultaneously considering peers' multiple specifications which reflect different properties of e-services. Different ontology based e-service profiles have been proposed to enhance service oriented framework for the total or partial automation of service mining, selection and composition, which are involved in either centralised or decentralised deployment of services. In this chapter, we propose a modelling based approach to design and develop a P2P based service coordination system and their components. The peer profiles are described with the WSMO (Web Service Modelling Ontology) standard, mainly for quality of service and geographic features of the e-services, which would be invoked by various peers. To fully explore the usability of service categorisation and mining, we implemented an ontology driven unified algorithm to select the most appropriate peers. The UOW-SWS prototype also shows that the enhanced peer coordination is more adaptive and effective in dynamic business processes. © 2009 Springer-Verlag Berlin Heidelberg.
Aslam, MA, Auer, S, Shen, J & Fähnrich, KP 2007, 'Bridging the semantic gap between business processes and semantic web services', Journal of Internet Technology, vol. 8, no. 4, pp. 433-443.
Bridging the semantic gap between business process models and semantic Web services becomes increasingly important in order to help automating business process integration in large organizations. Traditional workflow languages (such as BPEL4WS) support the modeling of business processes as syntax based compositions of Web services. When such processes are exported as Web services they as well expose syntactical interfaces. These syntactical interfaces allow only static composition and hence limit interactions between business partners. The obstacles of syntax based integration and composition can be addressed by enhancing business processes with semantics. This enables us to 1) edit and model the compositions of Web services on the basis of matching semantics 2) provide semantically enriched descriptions of business processes. In particular, it will support the dynamic and automated discovery, invocation and composition of business processes as semantic Web services. In this paper we present a mapping strategy that helps to overcome the syntactical limitations of BPEL processes by presenting them as OWL-S semantic Web services. The proposed strategy supports the mapping of BPEL process descriptions to complete OWL-S suite of ontologies (i.e. Profile, Process Model and Grounding ontologies). A prototypical implementation of the proposed approach has also been presented.
Shen, J, Grossmann, G, Yang, Y, Stumptner, M, Schrefl, M & Reiter, T 2007, 'Analysis of business process integration in Web service context', FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, vol. 23, no. 3, pp. 283-294.View/Download from: Publisher's site
Shen, J, Yang, Y & Yan, J 2007, 'A p2p based service flow system with advanced ontology-based service profiles', ADVANCED ENGINEERING INFORMATICS, vol. 21, no. 2, pp. 221-229.View/Download from: Publisher's site
Yang, Y, Lai, W, Shen, J, Huang, XD, Yan, J & Setiawan, L 2004, 'Effective visualisation of workflow enactment', ADVANCED WEB TECHNOLOGIES AND APPLICATIONS, vol. 3007, pp. 794-803.
Luo, YZ & Shen, J 2003, 'Synchro-net system: A Petri net model for higher-layer protocols', INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS, vol. 80, no. 10, pp. 1215-1225.View/Download from: Publisher's site
Luo, J, Shen, J & Gu, G 2000, 'From Petri nets to formal description techniques and protocol engineering', Ruan Jian Xue Bao/Journal of Software, vol. 11, no. 5, pp. 606-615.
Protocol is the lifeline of computer network. The rapid increasing of protocol complexity results in a discipline of protocol engineering. Based on an analysis of the contents and methods of protocol engineering activities and their interrelations, the paper first discusses main formal description techniques (FDTs) and their characteristics, compares corresponding strongpoints and weaknesses, and then leads to Petri nets based FDT. Secondly, the paper points out special advantages of the Petri nets based formal techniques and the current research difficulties in Petri nets based protocol engineering, among which protocol development oriented net tools are now very important research tasks. Thirdly, the paper summarizes international research advances in terms of OSI/RM layers and expounds research trends in this area. Finally the authors give fundamental methodologies for Petri nets based protocol engineering in protocol specification, verification and analysis, and computer-aided testing and implementation.
© 2017 by Taylor & Francis Group, LLC. The leverage of high-throughput technologies in biology area brings the academia and industry an enormous amount of 'omics' data. These data include genomics data and proteomics data. In this chapter we consider mostly on the genomics data. Benefited from the development of 'Big Data' area and also the domain knowledge driven by genomics data, two subsequent areas including precision medicine and cancer genomics, are discussed in this chapter. Meanwhile, we consider genomics data from the 'Big Data' landscape and give a comprehensive 'life cycle' on these data. Two significant and state-of-the-art cases in genomics data study are also presented. These two cases, which are ENCODE and CGHub, show inspiring and interesting results by the integration of big data analytics technology in genomics data. As the life science, biomedicine and health care sectors are at a turning point into data intensive science. Since we could benefit from the overwhelming genomics data, big data analytics shows us a promising potential to deliver a better understanding and improvement of our life.
Alismaili, S, Li, M & Shen, J 2016, 'Cloud computing adoption decision modelling for SMEs: From the PAPRIKA perspective' in Lecture Notes in Electrical Engineering, pp. 597-615.View/Download from: Publisher's site
© Springer Science+Business Media Singapore 2016. The popularity of cloud computing has been growing among enterprises since its inception. It is an emerging technology which promises competitive advantages, significant cost savings, enhanced business processes and services, and various other benefits. The aim of this paper is to propose a decision modelling using Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA) for the factors that have impact in SMEs cloud computing adoption process.
Chen, H, Shen, J, Wang, L & Chi, CH 2019, 'Towards Biological Sequence Data Service with Insights', Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018, pp. 2847-2854.View/Download from: Publisher's site
© 2018 IEEE. Testable prediction outcomes generated by computational models based on available databases are the primary sources helping to design biological experiments. Although numerous databases have been designed by collecting data either only from literature manually or together with prediction outcomes from computational models, there is currently not a comprehensive data service framework delivering better insights for these results. In this paper, we introduce a biological sequence data service towards delivering deeper insights and helping better biological experiments design. The service includes following major components: a comprehensive database for storing biological data, data analytics tools for analysing biological data, and computational models for delivering testable prediction outcomes. Specifically, we present this service in a framework for studies on host-pathogen interactions. The design of this framework aims to improve the understanding of host-pathogen interactions. The relationships of hierarchical databases and their working mechanism, specifically between PPIs and DDIs, are also presented in this framework. Finally, the preliminary and practical experiences of building computational model for prediction is discussed.
Jackson, TM, Nikolic, S, Shen, J & Xia, G 2019, 'Knowledge Sharing in Digital Learning Communities: A Comparative Review of Issues between Education and Industry', Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018, pp. 783-787.View/Download from: UTS OPUS or Publisher's site
© 2018 IEEE. Digital learning communities have become a focal point of organizational development. The education industry has begun to follow suit by using the same technologies to enhance the learning process through a deeper process of participation. These technological tools complement sound learning design to bring a wealth of benefits to students. These benefits are not without peril. New technological tools shift common issues of education into online environments. This article reviews recent implementations of digital communities and highlights their influencing factors. The factors are then connected to existing factors in knowledge management literature. The key factors found are A) Student interaction with the community, B) Interaction vs grades and C) Student experiences.
Li, F, Wu, J, Dong, F, Lin, J, Sun, G, Chen, H & Shen, J 2019, 'Ensemble Machine Learning Systems for the Estimation of Steel Quality Control', Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018, pp. 2245-2252.View/Download from: UTS OPUS or Publisher's site
© 2018 IEEE. Recent advances in the steel industry have encountered challenges in soliciting decision making solutions for quality control of products based on data mining techniques. In this paper, we present a steel quality control prediction system encompassing with real-world data as well as comprehensive data analysis results. The core process is cautiously designed as a regression problem, which is then best handled by grouping various learning algorithms with their massive resource of historical production datasets. The characteristics of the currently most popular learning models used in regression problem analysis are as well investigated and compared. The performance indicates our steel quality control prediction system based on ensemble machine learning model can offer promising result whilst delivering high usability for local manufacturers to address the production problem by aid of development of machine learning techniques. Furthermore, real-world deployment of this system is demonstrated and discussed. Finally, future directions and the performance expectation are pointed out.
Sun, W, Zhai, Y, Bao, T, Mudassar, M, Shen, J & Yang, K 2019, 'A microservices oriented edge computing framework for lvc simulation in the iot era', Proceedings of The 11th International Conference on Computer Modeling and Simulation ICCMS 2019, International Conference on Computer Modeling and Simulation, ACM, Australia, pp. 190-195.View/Download from: UTS OPUS or Publisher's site
© 2019 Association for Computing Machinery. Modeling and simulation are essential methods to better understand a complex system in the real world. Many simulation systems have strong demand for involving physical devices or equipment in the system to improve the fidelity. But most of the current cloud based simulation systems are designed for equipment with adequate resources and suffering from high latency for their centralized communication. Edge computing is getting much attention as a new paradigm for distributed systems involving heterogeneous devices and requiring real-time communication. However, edge computing is still in its initial stage and there is no consensus on the edge framework and implementation. To the best of our knowledge, no detailed studies have explored the edge-side simulation and modeling. In this paper, we study and design an edge-side simulation framework, which exploits light-weight microservices architecture to build scalable and real-time LVC (Live, Virtual and Constructive) simulations. Specifically, the application model is designed to illustrate how LVC simulation integrates with edge computing and cloud computing. The autonomous negotiation service and time synchronization services are discussed in details. Though it is a preliminary edge computing framework for LVC simulation, no similar research has been conducted for modeling and simulation using edge computing.
Xie, F, Yan, J & Shen, J 2018, 'A data dependency and access threshold based replication strategy for multi-cloud workflow applications', Lecture Notes in Computer Science, 11434 281-293. Hangzhou, China ICSOC 2018: Service-Oriented Computing - ICSOC 2018 Workshops, International Conference on Service-Oriented Computing, Spronger, China, pp. 281-293.View/Download from: UTS OPUS or Publisher's site
© Springer Nature Switzerland AG 2019. Data replication is one of the significant sub-areas of data management in cloud based workflows. Data-intensive workflow applications can gain great benefits from cloud environments and usually need data management strategies to manage large amounts of data. At the same time, multi-cloud environments become more and more popular. We propose a cost-effective and threshold-based data replication strategy with the consideration of both data dependency and data access times for data-intensive workflows in the multi-cloud environment. Finally, the simulation results show that our approach can greatly reduce total cost of data-intensive workflow applications by considering both of data dependency and data access times in multi-cloud environments.
Yong, B, Huang, L, Li, F, Shen, J, Wang, X & Zhou, Q 2019, 'GVM Based Copy-Dynamics Model for Electricity Load Forecast', Lecture Notes in Electrical Engineering, pp. 203-211.View/Download from: Publisher's site
© 2019, Springer Nature Singapore Pte Ltd. Electricity load forecast, as the core of electricity scheduling, plays a vita role in meeting the basic needs of modern human life. It has been widely studied in the past few decades. However, literature studies have shown that, as a problem of time series forecast, electricity forecast is prone to be influenced by many environmental factors, which result in lacking accuracy and stability in practice. In this paper, the General Vector Machine (GVM), a new type learning machine which was derived from Neural Network (NN) and Support Vector Machine (SVM), is applied into electricity load forecast. Meanwhile, copy-dynamics idea is introduced to electricity load forecast. Results reveal that, based on copy-dynamics, the maximum precision promotion of GVM reaches 71.7%, compared with BP. Hence, GVM and copy-dynamics models have great potential in electricity load forecast.
AlGhazi, A, Li, M, Cui, T, Fosso, S & Shen, J 2017, 'Exploration of the misalignment between business and IT strategic objectives in public-sector organisations: An empirical study in Saudi Arabia', Digital Transformation: Challenges and Opportunities (Lecture Notes in Business Information Processing), Workshop on E-Business, Springer, Seoul, South Korea, pp. 15-28.View/Download from: UTS OPUS or Publisher's site
© Springer Nature Switzerland AG 2018. Understanding business-IT strategy misalignment is an increasingly important area of research in digitalisation of different business sectors. However, there is currently a dearth of research investigations of misalignment between business and IT strategic objectives in public-sector organisations. Considering the nature of business, the structure of organisation, and the organisational resources of public-sector organisations, the investigation of business-IT misalignment can significantly enrich our theoretical exemplification of the relationship between business and IT in the public sector. Moreover, it provides some insights for managers to identify and avoid the possible pitfalls during the IT implementation process. Anchoring on the strategic alignment model, this research aims to identify and analyse the factors that contribute to business/IT strategy misalignment in Saudi Arabian public-sector organisations. Using a qualitative study design that included semi-structured interviews in five public-sector organisations in Saudi Arabia, our findings indicate that the human, operational, and IT system factors lead to business-IT strategy misalignment. This study also finds that those practical approaches for avoiding the misalignment in Saudi public-sector organisations sometimes lack structure and consistency.
AlGhazi, A, Li, M, Cui, T, Samuel, FW & Shen, J 2018, 'Misalignment between business and IT strategic objectives in Saudi Arabia public sector organisations', IoTBDS 2018 - Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security, International Conference on Internet of Things, Big Data and Security, SCITEPRESS, Funchal, Madeira, Portugal, pp. 212-220.View/Download from: UTS OPUS
Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved Business-IT strategy misalignment is increasingly an important area of concern and interest in organisations around the world including Saudi Arabia (SA). Indeed, the SA government has launched the National Digital Transformation Strategy for 2030 to support all public-sector organisations to improve efficiency and performance. This research aimed to identify and analyse the factors that contribute to business/IT strategy misalignment in Saudi public-sector organisations. This research focused emerged from the need to better understand the business and IT models incorporated in the organisations Saudi Arabia to achieve high performance, quality of service (QoS) and return of investment (ROI). Using a qualitative study design that included semi-structured interviews with eight executive and managerial staff from five public-sector organisations in Saudi Arabia, this study found human, operational and IT system factors all have the potential to contribute to business-IT strategy misalignment. It also found the approaches to misalignment avoidance in Saudi public-sector organisations sometimes lack structure and consistency.
Grieger, M, Ludwig, A & Shen, J 2018, 'Adding agility to software readiness assessment procedures - A case on digital transformation from the automotive industry', 26th European Conference on Information Systems: Beyond Digitization - Facets of Socio-Technical Change, ECIS 2018, European Conference on Information Systems, AIS, Portsmouth, UK.View/Download from: UTS OPUS
© 26th European Conference on Information Systems: Beyond Digitization - Facets of Socio-Technical Change, ECIS 2018. All Rights Reserved. In order to enable continuous and fast software development, manufacturers adopt agile development methodologies. In respect thereof, the organisation's operational processes need to be adapted to fit changing software project's needs. By means of a case study with an automotive OEM that introduces microservices (MS) architectures, the transformation of its software readiness assessment (SRA) procedure is investigated. The article introduces an artefact that builds upon standardized technical and organisational constructs inherent to MS projects. Further, by conceptually modelling a methodology is presented that guides an organisation in the transformation to implement agile SRA within its current operational infrastructure. The artefact is validated by means of three MS projects and respectively adapted. The findings suggest the artefact to be a useful intermediary step, but its successful implementation requires the integration of all contributing departments. The study deepens the knowledge about the transformation of an organisation's operational procedures by an empirical case and possible methodological paths.
Mahalle, A, Yong, J, Tao, X & Shen, J 2018, 'Data Privacy and System Security for Banking and Financial Services Industry based on Cloud Computing Infrastructure', Proceedings of the 2018 IEEE 22nd International Conference on Computer Supported Cooperative Work in Design, CSCWD 2018, International Conference on Computer Supported Cooperative Work in Design, IEEE, Nanjing, China, pp. 75-80.View/Download from: UTS OPUS or Publisher's site
© 2018 IEEE. Cloud computing architecture and infrastructure has received an acceptance from corporations and governments across the globe. Cloud computing helped to reduce cost of management of physical and technical infrastructure at the same time has made information systems available for locally globally deployed work force. Cloud computing infrastructure provides access to data and applications from any location and this has made organizations to keep evaluating privacy and security framework. Banking and financial services have data and applications which are internally developed to remain ahead of competition. This data and applications becomes the Intellectual Property (IP) that serves specific business processes and goals. When this data and applications can be accessed from remote locations, there may be a potential risks of data leakages and erosion of IP over a period of time. With an adoption of cloud computing, banking and financial services industry continues to be under strict regulatory and compliance framework to maintain privacy of data and security of systems. Privacy and security of cloud architecture infrastructure continues to be the challenge across the globe. In this paper, various aspects of cloud computing related to data privacy and system security for banking and financial services industry have been introduced.
Muhammad, A, Shen, J, Beydoun, G & Xu, D 2018, 'SBAR: A Framework to Support Learning Path Adaptation in Mobile Learning', Lecture Notes in Electrical Engineering, The 5th International Conference on Frontier Computing, Springer Nature, pp. 655-665.View/Download from: UTS OPUS
Sun, G, Cui, T, Dong, F, Xu, D, Shen, J, Chen, S & Lin, J 2018, '(WIP) Evaluation of a Cloud-Based System for Delivering Adaptive Micro Open Education Resource to Fresh Learners', IEEE International Conference on Cloud Computing, CLOUD, International Conference on Cloud Computing, San Francisco, CA, USA, pp. 586-589.View/Download from: UTS OPUS or Publisher's site
© 2018 IEEE. In this paper, we present an online computation approach implemented in a cloud-based system to assist open education resource (OER) providers and instructors dealing with the sparsity of data in micro OER recommendation. An algorithmic framework is provided to realize the novel micro OER recommendation system based on heuristic rules. These rules can also optimize the approaches to blending new-coming micro OERs into established learning paths. Comparing with different widely used recommender systems, our evaluation shows the proposed heuristic algorithms for online computation performs satisfactorily in terms of precision and recall values.
Sun, G, Cui, T, Xu, D, Shen, J & Chen, S 2018, 'A heuristic approach for new-item cold start problem in recommendation of micro open education resources', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Intelligent Tutoring Systems, Montreal, QC, Canada, pp. 212-222.View/Download from: UTS OPUS or Publisher's site
© Springer International Publishing AG, part of Springer Nature 2018. The recommendation of micro Open Education Resources (OERs) suffers from the new-item cold start problem because little is known about the continuously published micro OERs. This paper provides a heuristic approach to inserting newly published micro OERs into established learning paths, to enhance the possibilities of new items to be discovered and appear in the recommendation lists. It considers the accumulation and attenuation of user interests and conform with the demand of fast response in online computation. Performance of this approach has been proved by empirical studies.
Wu, J, Zhou, L, Cai, C, Shen, J, Lau, SK & Yong, J 2018, 'Data Fusion for MaaS: Opportunities and Challenges', Proceedings of the 2018 IEEE 22nd International Conference on Computer Supported Cooperative Work in Design, CSCWD 2018, International Conference on Computer Supported Cooperative Work in Design, IEEE, Nanjing, China, pp. 184-189.View/Download from: UTS OPUS or Publisher's site
© 2018 IEEE. Computer Supported Cooperative Work (CSCW) in design is an essential facilitator for the development and implementation of smart cities, where modern cooperative transportation and integrated mobility are highly demanded. Owing to greater availability of different data sources, data fusion problem in intelligent transportation systems (ITS) has been very challenging, where machine learning modelling and approaches are promising to offer an important yet comprehensive solution. In this paper, we provide an overview of the recent advances in data fusion for Mobility as a Service (MaaS), including the basics of data fusion theory and the related machine learning methods. We also highlight the opportunities and challenges on MaaS, and discuss potential future directions of research on the integrated mobility modelling.
Yong, B, Shen, J, Sun, H, Xu, Z, Liu, J & Zhou, Q 2018, 'GPU based simulation of collision detection of irregular vessel walls', Lecture Notes in Electrical Engineering, International Conference on Frontier Computing, Kuala Lumpur, Malaysia, pp. 443-453.View/Download from: UTS OPUS or Publisher's site
© Springer Nature Singapore Pte Ltd. 2018. Collision detection is a commonly used technique in the fields of computer games, physical simulation, virtual technology, computing and animation. When simulating the process of particle collision of ADS (Accelerator Driven Sub-Critical) system, complex and irregular vessel walls need to be considered. Generally, an irregular vessel wall is a curve surface, which cannot be defined as an exact mathematical function, and it is difficult to calculate the distance between particles and the wall directly. In this paper, we present an algorithm to perform collision detection between particles and irregular wall. When the number of particles reaches the level of 106, our algorithm implements a considerable improvement in performance if running on GPU, nearly 10 times faster than running on CPU. Results have demonstrated that our algorithm is promising.
Zhao, X, Yongchareon, S, Cho, N, Shen, J & Dewan, S 2018, 'Enabling intelligent business processes with context awareness', Proceedings - 2018 IEEE International Conference on Services Computing, SCC 2018 - Part of the 2018 IEEE World Congress on Services, pp. 153-160.View/Download from: UTS OPUS or Publisher's site
© 2018 IEEE. Sensing technologies provide system applications with the awareness of environmental conditions, customer behaviours, object movements, etc. Further, with such capability, system applications can be smart to intelligently adapt their responses to the changing conditions. With regard to business operations, these system applications ensure that business processes can run more intelligently and adaptively. These features will undoubtedly improve customer experience, enhance the reliability of service delivery and lower the operational cost for a more competitive and sustainable business. To enable context awareness to business process management, this paper proposes a conceptual method of depicting the context of a business process and the related mechanism of perceiving the contextual dynamics. A running example demonstrates the applicability of the proposed method and the improvements to process performance are evaluated using process simulations.
Alismaili, S, Li, M, Shen, J & He, Q 2017, 'A consumer-oriented decision-making approach for selecting the cloud storage service: From PAPRIKA perspective', Lecture Notes in Business Information Processing, pp. 1-12.View/Download from: Publisher's site
© Springer International Publishing AG 2017. In recent years there is a growth in the number of companies that offers cloud storage solutions. From user's perspectives, it is becoming a challenging task to choose which cloud storage to use and from whom, based on user's needs. In this context, no framework can evaluate the decision criteria for selection of cloud storage services. This paper proposes a solution to this problem by identifying the cloud storage criteria and introduces the PAPRIKA approach for measuring the criteria of cloud storage based on client's preference. This work demonstrated the applicability of the framework (decision model) by testing it with eleven users of cloud storage services. The results showed that the model could help users in making a more informative decision about cloud storage services.
Chen, C, Shen, J, Zhang, G, Zhao, R, Liu, J & Zhou, Q 2017, 'A Groundwater Management Tool for Solving the Pumping Yields Minimization Problem: A Case Study in the Heihe River Basin', Proceedings - 2016 International Conference on Advanced Cloud and Big Data, CBD 2016, pp. 289-295.View/Download from: Publisher's site
© 2016 IEEE. Declining groundwater levels caused by over-exploitation in the middle reaches of the Heihe River basin have raised concerns with respect to the sustainability of the aquifer system. The groundwater depletion in the Daman irrigation district is particularly serious suffering ∼20 m drawdown of groundwater level since 1980s. In this paper, a transient groundwater flow model was constructed and calibrated to simulate the groundwater dynamics in Daman irrigation district. A groundwater management tool has been developed to prevent further drawdown of groundwater level in conjunction with the flow model for this area. The response matrix method is used to transform a groundwater management problem into an optimization function. As a highly efficient and reliable method, the simplex method is used to solve the optimization problem. In the case of Daman irrigation district, the optimization problem is to maximize the pumping yields subject to the groundwater level constraints. To verify the effectiveness of the groundwater management tool, three different groundwater level constraints are assigned for the system control. The results indicate that the groundwater management tool is capable of identifying the optimal pumping yields for satisfying the given constraints. Further, the cultivated area which could be sustained by the optimized yearly pumping yields is calculated under the assumption of normal account of diverted water from the Heihe River. The results suggest two plausible solutions to approach the "sustainable pumping yield". Although this study focus on the Heihe River Basin, it illustrates a general modeling framework for the sustainability of groundwater flow systems.
Chen, H, Shen, J, Wang, L & Song, J 2017, 'Collaborative Data Analytics towards Prediction on Pathogen-Host Protein-Protein Interactions', 2017 IEEE 21ST INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD), IEEE 21st International Conference on Computer Supported Cooperative Work in Design (CSCWD), IEEE, Wellington, NEW ZEALAND, pp. 269-274.
Chen, H, Shen, J, Wang, L & Song, J 2017, 'Leveraging Stacked Denoising Autoencoder in Prediction of Pathogen-Host Protein-Protein Interactions', 2017 IEEE 6TH INTERNATIONAL CONGRESS ON BIG DATA (BIGDATA CONGRESS 2017), IEEE 6th International Congress on Big Data (BigData Congress), IEEE, Honolulu, HI, pp. 368-375.View/Download from: Publisher's site
Chen, H, Song, J, Sun, G, Shen, J & Wang, L 2017, 'Towards Elucidating the Structural Principles of Host-Pathogen Protein-Protein Interaction Networks: A bioinformatics survey', 2017 IEEE 6TH INTERNATIONAL CONGRESS ON BIG DATA (BIGDATA CONGRESS 2017), IEEE 6th International Congress on Big Data (BigData Congress), IEEE, Honolulu, HI, pp. 177-184.View/Download from: Publisher's site
He, Q, Zhu, X, Li, D, Wang, S, Shen, J & Yang, Y 2017, 'Cost-effective Big Data Mining in the Cloud: A Case Study with K-means', 2017 IEEE 10TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (CLOUD), 10th IEEE International Conference on Cloud Computing (CLOUD), IEEE, Honolulu, HI, pp. 74-81.View/Download from: Publisher's site
Sun, G, Cui, T, Beydoun, G, Chen, S, Xu, D & Shen, J 2017, 'Organizing Online Computation for Adaptive Micro Open Education Resource Recommendation', Advances in Web-Based Learning – ICWL 2017, International Conference on Web-Based Learning, Springer Link, Cape Town, South Africa, pp. 177-182.View/Download from: UTS OPUS
Our previous work, Micro Learning as a Service (MLaaS), aimed to deliver adaptive micro open education resources (OERs). However, relying solely on the offline computation, the recommendation lacks rationality and timeliness. It is also difficult to make the first recommendation to a new learner. In this paper we introduce the organization of the online computation of the MLaaS. It targets at solving the cold start problem due to the shortage of learner information and real-time updates of the learner-micro OER profile.
Sun, G, Cui, T, Beydoun, G, Shen, J & Chen, S 2016, 'Profiling and Supporting Adaptive Micro Learning on Open Education Resources', Proceedings of the Fourth International Conference on Advanced Cloud and Big Data (CBD), International Conference on Advanced Cloud and Big Data, IEEE, Chengdu, China, pp. 158-163.View/Download from: UTS OPUS or Publisher's site
It is found that learners prefer to use micro learning mode to conduct learning activities through open educational resources (OERs). However, adaptive micro learning is scarcely supported by current OER platforms. In this paper we focus on profiling an effective micro learning process which is central to establish the raw materials and set up rules for the final adaptive process. This work consists of two parts. First, we conducted an educational data mining and learning analysis study to discover the patterns and rules in micro learning through OER. Then based on its findings, we profiled features of both learners and OERs to reveal the full learning story in order to support the decision making process. Incorporating educational data mining and learning analysis, an cloud-based architecture for Micro Learning as a Service (MLaaS) was designed to integrate all necessary procedures together as a complete service for delivering micro OERs. The MLaaS also provides a platform for resource sharing and exchanging in peer-to-peer learning environment. Working principle of a key step, namely the computational decision-making of micro OER adaptation, was also introduced
Sun, G, Cui, T, Shen, J, Xu, D & Beydoun, G 2017, 'Ontological Learner Profile Identification for Cold Start Problem in Micro Learning Resources Delivery', IEEE 17th International Conference on Advanced Learning Technologies, IEEE, Timisoara, Romania, pp. 16-20.View/Download from: UTS OPUS or Publisher's site
Open learning is a rising trend in the educational sector and it attracts millions of learners to be engaged to enjoy massive latest and free open education resources (OERs). Through the use of mobile devices, open learning is often carried out in a micro learning mode, where each unit of learning activity is commonly shorter than 15 minutes. Learners are often at a loss in the process of choosing OER leading to their long term objectives and short term demands. Our pilot work, namely MLaaS, proposed a smart system to deliver personalized OER with micro learning to satisfy their real-time needs, while its decision-making process is scarcely supported due to the lack of historical data. Inspired by this, MLaaS now embeds a new solution to tackle the cold start problem, by opening up a brand new profile for each learner and delivering them the first resources in their fresh start learning journey. In this paper, we also propose an ontology-based mechanism for learning prediction and recommendation.
Sun, G, Cui, T, Xu, D, Chen, H, Chen, S & Shen, J 2017, 'Assisting Open Education Resource Providers and Instructors to Deal With Cold Start Problem in Adaptive Micro Learning: a Service Oriented Solution', 2017 IEEE INTERNATIONAL CONFERENCE ON SERVICES COMPUTING (SCC), IEEE International Conference on Services Computing (SCC), IEEE, Honolulu, HI, pp. 196-203.View/Download from: Publisher's site
Xie, F, Yan, J & Shen, J 2017, 'Towards Cost Reduction in Cloud-Based Workflow Management through Data Replication', 2017 FIFTH INTERNATIONAL CONFERENCE ON ADVANCED CLOUD AND BIG DATA (CBD), 5th International Conference on Advanced Cloud and Big Data (CBD), IEEE, SHANGHAI, PEOPLES R CHINA, pp. 94-99.View/Download from: Publisher's site
Xu, Z, Dong, F, Jin, J, Luo, J & Shen, J 2017, 'GScheduler: Optimizing Resource Provision by Using GPU Usage Pattern Extraction in Cloud Environments', 2017 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), IEEE International Conference on Systems, Man, and Cybernetics (SMC), IEEE, Banff, CANADA, pp. 3225-3230.View/Download from: UTS OPUS
Yong, B, Chen, H, Xu, Z, Tian, Y, Shen, J & Zhou, Q 2017, 'Neural network model with monte carlo algorithm for electricity demand forecasting in Queensland', ACM International Conference Proceeding Series.View/Download from: Publisher's site
© 2017 ACM. With the rapid growth over the past few decades, people are consuming more and more electrical energies. In order to solve the contradiction between supply and demand to minimize electricity cost, it is necessary and useful to predict the electricity demand. In this paper, we apply an improved neural network algorithm to forecast the electricity, and we test it on a collected electricity demand data set in Queensland to verify its performance. There are two contributions in this paper. Firstly, comparing with backpropagation (BP) neural network, the results show a better performance on this improved neural network. Secondly, the performance on various hidden layers shows that different dimension of hidden layer in this improved neural network has little impact on the Queensland's electricity demand forecasting.
Al-Isma'Ili, S, Li, M, He, Q & Shen, J 2016, 'Cloud computing services adoption in Australian SMEs: A firm-level investigation', Pacific Asia Conference on Information Systems, PACIS 2016 - Proceedings.
Cloud computing services can boost the competitiveness of Small and Medium-sized Enterprises (SMEs) and leverage countries' economies. In the Australian context, there is an emerging trend that SMEs begin to embrace cloud technology in their traditional business activities. However, prior studies did not pay much attention to investigating the factors that influence the cloud computing adoption among Australian SMEs. To fill the research gap, this paper investigates the influential factors that affect the decision on adopting cloud computing services for Australian SMEs. Protocol data collected from fifteen firm-level semi-structured interviews with practitioners are presented and discussed. The protocol analysis indicates that various factors are important to the adoption of cloud computing services for Australian SMEs, such as security concerns, cost savings, and privacy due to geo-restrictions. Furthermore, this study confirms the insignificance of complexity and competitive pressure factors in the adoption of cloud computing among Australian SMEs. These findings have imperative implications to scholars and practitioners alike in the cloud computing research and applications areas.
Al-Isma'Ili, S, Li, M, Shen, J & He, Q 2016, 'Cloud computing adoption determinants: An analysis of Australian SMEs', Pacific Asia Conference on Information Systems, PACIS 2016 - Proceedings.
In Australia, there is an emerging tendency among SMEs towards the adoption of cloud computing. However, there are limited studies investigating the factors that influence cloud computing adoption within Australian SMEs. To fill the research vacuum, we developed a research model based on the diffusion of innovation theory (DOI), the technology-organisation-environment (TOE) framework, and our prior exploratory study to investigate the determinants that influence the adoption of cloud computing. An organizational-level survey was conducted across Australia to collect data from technology decision makers in SMEs. Data collected from 203 firms are used to test the related hypotheses. This study contributes a statistically validated model of the influential determinants of cloud computing adoption. Data analysis indicates that Technological Factors (cost savings, relative advantages, compatibility, and trialability), Organizational Factors (firm size, top management support, innovativeness of the firm, and IS knowledge), and Environmental Factors (market scope and external computing support) were found to be determinants of the adoption of cloud computing services. Benefits of the findings are twofold. First, they provide knowledge about cloud computing determinants in the Australian marketplace. Second, they provide policy planners and SMEs' decision makers with insights and directions for successful adoption of cloud computing technology.
Chen, C, Shen, J, Zhang, G, Zhao, R, Liu, J & Zhou, Q 2016, 'A groundwater management tool for solving the pumping yields minimization problem', 2016 FOURTH INTERNATIONAL CONFERENCE ON ADVANCED CLOUD AND BIG DATA (CBD 2016), 4th International Conference on Advanced Cloud and Big Data (CBD), IEEE, Chengdu, PEOPLES R CHINA, pp. 289-295.View/Download from: Publisher's site
Chen, H, Shen, J, Wang, L & Song, J 2016, 'Towards Data Analytics of Pathogen-Host Protein-Protein Interaction: A survey', 2016 IEEE INTERNATIONAL CONGRESS ON BIG DATA - BIGDATA CONGRESS 2016, IEEE International Congress on Big Data (BigData Congress), IEEE, San Francisco, CA, pp. 377-388.View/Download from: Publisher's site
Muhammad, A, Zhou, Q, Beydoun, G, Xu, D & Shen, J 2016, 'Learning Path Adaptation in Online Learning Systems', Proceedings of the IEEE 20th International Conference on Computer Supported Cooperative Work in Design (CSCWD), International Conference on Computer Supported Cooperative Work in Design, IEEE, Nanchang, China, pp. 421-426.View/Download from: UTS OPUS or Publisher's site
Learning path in online learning systems refers to a sequence of learning objects which are designated to help the students in improving their knowledge or skill in particular subjects or degree courses. In this paper, we review the recent research on learning path adaptation to pursue two goals, first is to organize and analyze the parameter of adaptation in learning path; the second is to discuss the challenges in implementing learning path adaptation. The survey covers the state of the art and aims at providing a comprehensive introduction to the learning path adaptation for researchers and practitioners
Sun, Z, Jin, H, Yong, J, Al-Ismaili, S, Li, C & Shen, J 2016, 'A High Availability Application Service Platform for Nuclear Power Enterprises', 2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 20th IEEE International Conference on Computer Supported Cooperative Work in Design (CSCWD), IEEE, Nanchang, PEOPLES R CHINA, pp. 613-618.
Topi, H, Carvalho, JA, Karsten, H, Tan, BCY, Brown, SA, Donnellan, B, Shen, J & Thouin, M 2016, 'MSIS 2016: A comprehensive update of graduate level curriculum recommendation in Information Systems', AMCIS 2016: Surfing the IT Innovation Wave - 22nd Americas Conference on Information Systems.
The process to revise MSIS 2006, the master's level curriculum recommendation for Information Systems, is getting close to completion. In spring and summer 2016, the joint AIS/ACM task force will continue the process of soliciting comments from various stakeholders, including the academic IS community and employers. The purpose of the AMCIS panel is to give the audience an update of the status of the MSIS 2016 revision process and provide the task force with feedback regarding the draft document. A significant portion of the session will be reserved for conversation. The task force is proposing significant changes to the curriculum content and structure, including the new curriculum's focus on specifying desired graduate competencies instead of articulating courses or knowledge areas/units. Some of the changes are a reflection of the changes in the process used to revise the curriculum: MSIS 2016 will be a result of a truly global process.
Topi, H, Karsten, H, Brown, SA, Carvalho, JA, Donnellan, B, Shen, J, Tan, BCY & Thouin, MF 2016, 'Competency-based approach to information systems program development: Guidance from the MSIS 2016 global competency model', 2016 AIS SIGED International Conference on IS Education and Research.
© 2016 CURRAN-CONFERENCE. All rights reserved. The panel has three objectives: First, it will present multiple perspectives on competency-driven approaches to developing and evaluating degree programs in Information Systems and compare the competency-driven approach to earlier, teaching topic or body of knowledge-driven approaches. Second, it will introduce the (nearly) completed version of the MSIS 2016 global competency model to the members of the global IS community and celebrate IS community's efforts to improve the quality of graduate education. Third, the panel will discuss the essential role the competency-driven approach has as a foundation of MSIS 2016.
Alismaili, S, Li, M, Shen, J & He, Q 2015, 'A multi perspective approach for understanding the determinants of cloud computing adoption among Australian SMEs', ACIS 2015 Proceedings - 26th Australasian Conference on Information Systems.
© 2015 Salim Al Ismaili, Dr. Mengxiang Li, Associate Professor Jun Shen, Dr. Qiang He. Cloud computing is proved to be an effective computing technology for organisations through the advantages that it offers such as IT technical agility and scalability, enhancing businesses processes, and increasing enterprises competitiveness. In Australia, there is an emerging trend that small and medium-sized enterprises (SMEs) begin to adopt this technology in the conventional working practices. However, there is a dearth of prior studies on examining the factors that influence the cloud computing adoption among Australian SMEs. To fill the empirical vacuum, this research-in-progress proposes an integrated framework for examining the determinants of cloud computing service adoption with the consideration of the unique characteristics of Australian SMEs, such as relatively low adoption of cloud computing services, less innovative, and limited knowledge about cloud computing and its benefits and hindrances. To this end, we are conducting consecutive studies to investigate this research issue. An exploratory interview study will be applied to observe and verify the characteristics of Australian SMEs toward the cloud computing adoption. This is followed by an organisational level survey that examines the effects of determinants on cloud computing adoption. Finally, a decision model for cloud computing adoption among Australian SMEs will be developed by using a Multi Criteria Decision Approach (MCDA) through rating, prioritising, and ranking of various criteria and alternatives available to the decision makers. Adopting the mixed-method research fashion, this research-in-progress intends to make significant implications to scholars and practitioners alike in the cloud computing research and applications areas.
Chen, H, Zhao, H, Shen, J, Zhou, R & Zhou, Q 2015, 'Supervised Machine Learning Model for High Dimensional Gene Data in Colon Cancer Detection', 2015 IEEE INTERNATIONAL CONGRESS ON BIG DATA - BIGDATA CONGRESS 2015, IEEE International Congress on Big Data, IEEE, New York, NY, pp. 134-141.View/Download from: Publisher's site
Karsten, H, Topi, H, Brown, SA, Carvalho, JA, Donnellan, B, Shen, J, Tan, BCY & Thouin, MF 2015, 'Master's degree programs in information systems: A global view', AIS SIGED: IAIM International Conference.
In this paper, we present an analysis of 254 master's degree programs in Information Systems, offered by 229 universities in 32 countries. The entry requirements usually include a Bachelor's degree in IS or a related subject. In some countries such as USA any kind of Bachelor's degree is acceptable. In a few countries significant relevant work experience can replace or supplement the BSc. The duration of the degrees varies between one to two years, with the student workload between 1350-3200 hours. If we take into consideration the differences in entering the program (from none to four years of IS studies), the gap grows considerably. Most programs require course work in both computing and a domain of practice (such as business), but some have no requirements related to the domain of practice and still others have only modest computing requirements. Degrees with a professional orientation emphasize industry projects and internships, while in several countries a thesis is an essential part of the degree thereby preparing for further studies. A thesis also trains for reading and writing academic papers, thus enabling graduates to tap into current research in their daily work. The variation amongst programs presents a concern for the image of IS as a profession and a challenge for recruiters. The results are discussed in the context of an ongoing project to revise the graduate level model curriculum in Information Systems, with a particular emphasis on the IS profession.
Sun, G & Shen, J 2013, 'Enhancing Teamwork Performance in Mobile Cloud-Based Learning', ADVANCES IN WEB-BASED LEARNING, 12th International Conference on Advances in Web-Based Learning (ICWL), SPRINGER-VERLAG BERLIN, TAIWAN, pp. 107-117.View/Download from: Publisher's site
Sun, G, Cui, T, Beydoun, G, Guo, W, Xu, D & Shen, J 2015, 'Micro learning adaptation in MOOC: A software as a service and a personalized learner model', Advances in Web-Based Learning -- ICWL 2015, International Conference on Web-Based Learning, Springer, Guangzhou, China, pp. 174-184.View/Download from: UTS OPUS or Publisher's site
Micro learning is gradually becoming a common learning mode in massive open online course learning (MOOC). We illustrate a research strategy to formalize and customize micro learning resources in order to meet personal demands at the real time. This smart micro learning environment can be organized by a Software as a Service (SaaS) we newly designed, in which educational data mining technique is mainly employed to understand learners learning behaviors and recognize learning resource features in order to identify potential micro learning solutions. A learner model with regards to internal and external factors is also proposed for personalization in micro MOOC learning context.
Sun, G, Cui, T, Chen, S, Guo, W & Shen, J 2015, 'MLaaS: A Cloud System for Mobile Micro Learning in MOOC', Proceedings - 2015 IEEE 3rd International Conference on Mobile Services, MS 2015, pp. 120-127.View/Download from: Publisher's site
© 2015 IEEE. Mobile learning in massive open online course (MOOC) differs evidently from its traditional ways as it relies more on collaboration and becomes fragmented. We introduce a cloud-based system which can organize learners into a better teamwork context and customize micro learning resources in order to meet personal demands in real time. Particularly, a smart micro learning environment can be built by a newly designed SaaS, in which educational data mining techniques are mainly employed to understand learners' behaviors and recognize learning resource features.
Sun, G, Cui, T, Chen, S, Guo, W & Shen, J 2015, 'MLaaS: A Cloud System for Mobile Micro Learning in MOOC', 2015 IEEE THIRD INTERNATIONAL CONFERENCE ON MOBILE SERVICES MS 2015, IEEE 3rd International Conference on Mobile Services MS, IEEE, New York, NY, pp. 120-127.View/Download from: Publisher's site
Sun, G, Cui, T, Li, K-C, Xu, D, Chen, S, Shen, J & Guo, W 2015, 'Towards Bringing Adaptive Micro Learning into MOOC Courses', 15TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED LEARNING TECHNOLOGIES (ICALT 2015), 15th IEEE International Conference on Advanced Learning Technologies (ICALT), IEEE, Hualien, TAIWAN, pp. 462-463.View/Download from: Publisher's site
Sun, G, Cui, T, Yang, J, Shen, J & Chen, S 2015, 'Drawing Micro Learning into MOOC: Using Fragmented Pieces of Time to Enable Effective Entire Course Learning Experiences', PROCEEDINGS OF THE 2015 IEEE 19TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD), IEEE 19th International Conference on Computer Supported Cooperative Work in Design (CSCWD), IEEE, Calabria, ITALY, pp. 308-313.
Topi, H, Karsten, H, Brown, SA, Carvalho, JA, Donnellan, B, Shen, J, Tan, BCY & Thouin, MF 2015, 'Current msis students' views on program outcomes', AIS SIGED: IAIM International Conference.
This paper reports the results of a pilot survey sent to current specialized master's students in Information Systems at several universities around the world. The survey was developed to support the MSIS revision process, but the results will also provide insights on the perceptions of current IS master's students regarding their current degree program. The results suggest that the respondents valued individual foundational skills and high-level business competences more than technical or lower-level managerial competences. The study utilized competence specifications from the European e-CF 3.0 model, which was useful and performed well as a competence framework.
Topi, H, Karsten, H, Brown, SA, Carvalho, JA, Donnellan, B, Shen, J, Tan, BCY & Thouin, MF 2015, 'Revising the MSIS 2016 model curriculum: Status Update and panel discussion', AIS SIGED: IAIM International Conference.
This panel discussion will provide an update of the ongoing work to revise the ACM/AIS graduate level curriculum recommendation for Information Systems (MSIS). The panel will consist of the members of the task force, who will report on a) changes in the direction of the task force's work since summer 2015 position paper; b) results of the fall 2015 data collection; and c) key decisions regarding the curriculum architecture made by the time of the panel. A major part of the panel will be reserved for open discussion and participant feedback, which will directly impact the work of the task force.
Wang, L, Shen, J & Luo, J 2015, 'Bio-inspired cost-aware optimization for data-intensive service provision', CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, WILEY, pp. 5662-5685.View/Download from: Publisher's site
Wang, L, Shen, J & Luo, J 2015, 'Multi-objective Ant Colony System for Data-Intensive Service Provision', Proceedings - 2014 2nd International Conference on Advanced Cloud and Big Data, CBD 2014, pp. 45-52.View/Download from: Publisher's site
© 2014 IEEE. Data-intensive services have become one of the most challenging applications in cloud computing. The classical service composition problem will face new challenges as the services and correspondent data grow. A typical environment is the large scale scientific project AMS, which we are processing huge amount of data streams. In this paper, we will resolve service composition problem by considering the multi-objective data-intensive features. We propose to apply ant colony optimization algorithms and implemented them with simulated workflows in different scenarios. To evaluate the proposed algorithm, we compared it with a multi-objective genetic algorithm with respect to five performance metrics.
Sun, G & Shen, J 2014, 'Collaborative Learning through TaaS: a Mobile System for Courses over the Cloud', 2014 14TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED LEARNING TECHNOLOGIES (ICALT), 14th IEEE International Conference on Advanced Learning Technologies (ICALT) - Advanced Technologies for Supporting Open Access to Formal and Informal Learning, IEEE, Athens, GREECE, pp. 278-280.View/Download from: Publisher's site
Wang, L, Shen, J & Luo, J 2014, 'Impacts of Pheromone Modification Strategies in Ant Colony for Data-Intensive Service Provision', 2014 IEEE 21ST INTERNATIONAL CONFERENCE ON WEB SERVICES (ICWS 2014), 21st IEEE International Conference on Web Services (ICWS), IEEE, Anchorage, AK, pp. 177-184.View/Download from: Publisher's site
Wang, L, Shen, J, Zhou, Q & Beydoun, G 2014, 'Ant-inspired multi-phase and multi-party negotiations in the data-intensive service provision', Proceedings - 2014 IEEE International Conference on Services Computing, SCC 2014, IEEE International Conference on Services Computing, IEEE, Anchorage, AK, USA, pp. 211-218.View/Download from: UTS OPUS or Publisher's site
© 2014 IEEE. The rapid proliferation of enormous sources of digital data and the development of cloud computing have led to greater dependence on data-intensive services. Each service may actually request or create a large amount of data sets. To compose these services will be more challenging. Issues of autonomy, scalability, adaptability, and robustness, become difficult to resolve. In order to automate the process of reaching an agreement in data-intensive service provision, the ant-inspired negotiation mechanism is considered in this paper. There are two-stage negotiation procedures in our model, which will provide effective and efficient service selection for service composers. We also present a multi-phase, multi-party negotiation protocol, where the ant colony system is applied for selecting the services. The experimental results show that our ant-inspired negotiation approach can facilitate the data-intensive service provision.
Dong, F, Luo, J, Zhu, X, Wang, Y & Shen, J 2013, 'A Personalized Hybrid Recommendation System Oriented to E-Commerce Mass Data in the Cloud', 2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013), IEEE International Conference on Systems, Man, and Cybernetics (SMC), IEEE, Manchester, ENGLAND, pp. 1020-1025.View/Download from: Publisher's site
Sun, G & Shen, J 2013, 'Facilitating Collaborative Learning in TaaS: a Mobile Cloud System for Enhancing Teamwork Performance', 2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013), IEEE International Conference on Systems, Man, and Cybernetics (SMC), IEEE, Manchester, ENGLAND, pp. 681-686.View/Download from: Publisher's site
Sun, G & Shen, J 2013, 'Teamwork as a Service: a Cloud-based System for Enhancing Teamwork Performance in Mobile Learning', 2013 IEEE 13TH INTERNATIONAL CONFERENCE ON ADVANCED LEARNING TECHNOLOGIES (ICALT 2013), 13th IEEE Annual International Conference on Advanced Learning Technologies (ICALT), IEEE, Beijing Normal Univ, Beijing, PEOPLES R CHINA, pp. 376-378.View/Download from: Publisher's site
Sun, G, Shen, J, Luo, J & Yong, J 2013, 'Evaluations of Heuristic Algorithms for Teamwork-Enhanced Task Allocation in Mobile Cloud-Based Learning', PROCEEDINGS OF THE 2013 IEEE 17TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD), IEEE 17th International Conference on Computer Supported Cooperative Work in Design (CSCWD), IEEE, Whistler, CANADA, pp. 299-304.
Sun, Z, Shen, J & Yong, J 2013, 'A novel approach to data deduplication over the engineering-oriented cloud systems', INTEGRATED COMPUTER-AIDED ENGINEERING, IOS PRESS, pp. 45-57.View/Download from: Publisher's site
Wang, L & Shen, J 2013, 'Economical data-intensive service provision supported with a modified genetic algorithm', 2013 IEEE INTERNATIONAL CONGRESS ON BIG DATA, IEEE International Congress on Big Data, IEEE, Santa Clara, CA, pp. 355-362.View/Download from: Publisher's site
Wang, L, Luo, J, Shen, J & Dong, F 2013, 'Cost and time aware ant colony algorithm for data replica in Alpha Magnetic Spectrometer experiment', 2013 IEEE INTERNATIONAL CONGRESS ON BIG DATA, IEEE International Congress on Big Data, IEEE, Santa Clara, CA, pp. 247-254.View/Download from: Publisher's site
Wang, L, Shen, J & Beydoun, G 2013, 'Enhanced ant colony algorithm for cost-aware data-intensive service provision', Proceedings - 2013 IEEE 9th World Congress on Services, SERVICES 2013, IEEE World Congress on Services, IEEE, Santa Clara, CA, USA, pp. 227-234.View/Download from: UTS OPUS or Publisher's site
Huge collections of data have been created in recent years. Cloud computing has been widely accepted as the next-generation solution to addressing data-proliferation problems. Because of the explosion in digital data and the distributed nature of the cloud, as well as the increasingly large number of providers in the market, providing efficient cost models for composing data-intensive services will become central to this dynamic market. The location of users, service composers, service providers, and data providers will affect the total cost of service provision. Different providers will need to make decisions about how to price and pay for resources. Each of them wants to maximize its profit as well as retain its position in the marketplace. Based on our earlier work, this paper addresses the effect of data intensity and the communication cost of mass data transfer on service composition, and proposes a service selection algorithm based on an enhanced ant colony system for data-intensive service provision. In this paper, the data-intensive service composition problem is modeled as an AND/OR graph, which is not only able to deal with sequence relations and switch relations, but is also able to deal with parallel relations between services. In addition, the performance of the service selection algorithm is evaluated by simulations. © 2013 IEEE.
Wang, L, Shen, J, Di, C, Li, Y & Zhou, Q 2013, 'Towards minimizing cost for composite data-intensive services', PROCEEDINGS OF THE 2013 IEEE 17TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD), IEEE 17th International Conference on Computer Supported Cooperative Work in Design (CSCWD), IEEE, Whistler, CANADA, pp. 293-298.
Wang, L, Shen, J, Luo, J & Dong, F 2013, 'An Improved Genetic Algorithm for Cost-Effective Data-Intensive Service Composition', 2013 NINTH INTERNATIONAL CONFERENCE ON SEMANTICS, KNOWLEDGE AND GRIDS (SKG), 9th International Conference on Semantics, Knowledge and Grids (SKG), IEEE, Beijing, PEOPLES R CHINA, pp. 105-112.View/Download from: Publisher's site
Dong, F, Luo, J, Song, A, Cao, J & Shen, J 2012, 'An effective data aggregation based adaptive long term CPU load prediction mechanism on computational grid', FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF GRID COMPUTING AND ESCIENCE, ELSEVIER SCIENCE BV, pp. 1030-1044.View/Download from: Publisher's site
Ghaffar, ARA, Beydoun, G, Shen, J, Tibben, W & Xu, D 2012, 'A synthesis of a knowledge management framework for sports event management', ICSOFT 2012 - Proceedings of the 7th International Conference on Software Paradigm Trends, International Conference on Software Paradigm Trends, Scitepress, Rome, Italy, pp. 494-499.View/Download from: UTS OPUS
Due to rapid social development in Asia, sports events have grown larger and many new countries are also hosting them for their first time. In addition to required increase in expenditures and more efficient management, various instances of inadequate planning highlighted the needs for more effective and better sustainable structures to support knowledge transfer between organizers, from one event to the next. The research presented in this paper aims to facilitate the deployment of systematic knowledge management practices to sports event management, to enable sustainable planning. The research in this paper synthesizes is carried out on the Malaysian Games as an example of a sports event management. Furthermore, we introduce knowledge management (KM) framework that was developed based on studies and observations of processes and activities in this organization. The focus is on knowledge that is key to the success of the Malaysian Games and that which can be used to the development of the organization and in future games.
Kamaruddin, LA, Shen, J & Beydoun, G 2012, 'Evaluating usage of WSMO and OWL-S in semantic web services', Conferences in Research and Practice in Information Technology Series, Conferences in Research and Practice in Information Technology (CRPIT), Association for Computing Machinery (ACM), Melbourne, Australia, pp. 53-58.View/Download from: UTS OPUS
Applying ontologies is the most promising approach to semantically enrich Web services. To facilitate this, two efforts contributed the most in enabling the creation of ontologies: OWL-S from the US and WSMO in Europe. These two compete and promote their ontologies from the design perspective, reflecting their inventors' bias but not offering much help to Web service developers using them. To bypass existing biases and enable evaluation of ontologies expressed in these two languages, this paper provides a study of the two important facilitators, OWL-S and WSMO, surveying their usage in several SWS Projects and identifying their respective and outstanding gaps. The paper then proposes a set of evaluation criteria for usage measurement on the two prominent SWS ontologies. © 2012, Australian Computer Society, Inc.
Wang, L & Shen, J 2012, 'Towards bio-inspired cost minimisation for data-intensive service provision', Proceedings - 2012 IEEE 1st International Conference on Services Economics, SE 2012, pp. 16-23.View/Download from: Publisher's site
The world is filled with an unimaginably vast amount of digital information which is getting even vaster and even growing more rapidly. The enormous new data is impacting every area of our society. The real strategic value of the data can determine what will happen and what can be discovered in the future. To better use the so called "Big Data", automatic business process or workflow is needed to process large quantity of data. Biological systems present fascinating features, such as autonomy, scalability, adaptability, and robustness. The bio-inspired concepts and mechanisms have been successfully applied to service oriented systems. In this study, by reviewing a number of studies which applied biological concepts and principles to solve problems of service provision, we proposed a bio-inspired cost minimisation mechanism for dataintensive service provision. It utilizes bio-inspired mechanisms to search and find the optimal data service solution considering cost of data management and service maintenance. The newly composed data-intensive service will be a timely contribution to "Big Data" research. © 2012 IEEE.
Wang, L, Shen, J & Yong, J 2012, 'A survey on bio-inspired algorithms for web service composition', Proceedings of the 2012 IEEE 16th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2012, pp. 569-574.View/Download from: Publisher's site
Web service composition has become a promising technology in a variety of e-science or e-business areas. There are a variety of models and methods to deal with this issue from different aspects. Bio-inspired algorithms are becoming main approaches and solutions. This paper reviews the current researches on web service composition based on bio-inspired algorithms, such as Ant Colony Optimization (ACO), Genetic Algorithm(GA), Evolutionary Algorithm (EA) and Particle Swarm Optimization(PSO). By analyzing and investigating different approaches, this paper gives an overview about the researches on bio-inspired algorithm in web service composition and point out future directions. © 2012 IEEE.
Ahmed, W, Aslam, MA, Shen, J & Yong, J 2011, 'A light weight approach for ontology generation and change synchronization between ontologies and source relational databases', Proceedings of the 2011 15th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2011, pp. 208-214.View/Download from: Publisher's site
Ontology is specification of shared conceptualization and is building block of the semantic Web. Ontology building requires a detailed domain analysis that in turn requires financial resources, intensive domain knowledge and time. Most of industrial data is present in relational databases and a relational database schema represents a domain model. An ontology built from this schema can represent concepts and relationships that are present in domain of discourse. However, databases are not static and their schema evolves over time. Once a database schema is changed, these changes in schema should also be incorporated in ontology, generated from this database. The possible solution of regenerating a new ontology from changed database schema is not feasible because this will result in loss of manual changes of ontology. In this paper we present an approach that can be used to generate ontology from RDBs and to synchronize the generated ontology with changes occurred in the same database. We also present the prototypical implementation of the proposed approach as Proté gé plug-in (i.e. DATAONTO) that can be used to generate ontology from database and to synchronize the ontology with the original database. © 2011 IEEE.
Al-Hmouz, A, Shen, J, Yan, J & Al-Hmouz, R 2011, 'Modeling mobile learning system using ANFIS', Proceedings of the 2011 11th IEEE International Conference on Advanced Learning Technologies, ICALT 2011, pp. 378-380.View/Download from: Publisher's site
Personalisation is becoming more important in the area of mobile learning. Learner model is logically partitioned into smaller elements or classes in the form of learner profiles, which can represent the entire learning process. Machine learning techniques have the ability to detect patterns from complicated data and learn how to perform activities based on learner profiles. This paper focuses on a systematic approach in reasoning the learner contexts to deliver adaptive learning content. A fuzzy rule base model that has been proposed in related work is found insufficient in deciding all possible conditions. To tackle this problem, this paper adopts the Adaptive Neuro-Fuzzy Inference System (ANFIS) approach to determine all possible conditions. ANFIS uses the hybrid (least-squares method and the back propagation gradient descent method) as learning mechanism for the Neural Network to determine the incompleteness in the decision made by human experts. The simulating results by Matlab indicate that the performance of ANFIS approach is valuable and easy to implement. © 2011 IEEE.
Ghaffar, ARA, Beydoun, G, Shen, J & Tibben, W 2011, 'Towards knowledge management in sports event management: Context Analysis of Malaysian biannual games with CommonKADS', ICSOFT 2011 - Proceedings of the 6th International Conference on Software and Database Technologies, International Conference on Software and Data Technologies, Seville, Spain, pp. 377-383.View/Download from: UTS OPUS
Context Analysis (CA) is typically used as an early phase preceding the development of a knowledge-based systems in order to indicate how the system should interact with its environment and the various stakeholders. We undertake a detailed context analysis of business processes of the Malaysian Games (MG) to highlight blind spots of the process and enable the identification of an initial sports event knowledge management (KM) framework. Firstly, our CommonKADS driven analysis highlights how we can improve the business process and enable the organization to develop, distribute and apply its knowledge resources effectively. Secondly, the paper highlights specific features about the domain of sports events management and accordingly presents a set of recommendations to extend the CA of CommonKADS to improve its applicability to Sports Events Management in general.
Henderson-Sellers, B, Shen, J, Ghassan, B, Yuan, S & Low, GC 2011, 'Towards peer selection in a semantically-enriched service execution framework with QoS specifications', Proceedings of The Sixth International Conference on Internet and Web Applications and Services (ICIW2011), International Conference on Internet and Web Applications and Services, ThinkMind, St Maarten, The Netherlands Antilles, pp. 201-206.View/Download from: UTS OPUS
This paper promotes an ontology-based multi agent system (MAS) framework to facilitate Peer-to-Peer (P2P) service selection with multiple service properties. P2P-based service has emerged as an important new field in the distributed computing arena. It focuses on intensive service sharing, innovative applications and compositions, and, in some cases, high performance orientation. However, one of the remaining challenges for the P2P-based service composition process is how to effectively discover and select the most appropriate peers to execute the service applications when considering multiple properties of the requested services. By introducing an ontology, different ontology-based e-service profiles can be proposed to facilitate handling multiple properties and to enhance the service oriented process in order to achieve the total or partial automation of service discovery, selection and composition. In this paper, we present a conceptual framework for peer selection with a preliminary mathematical model and a selection process, so as to enhance the P2P-based service coordination system and its components.
Ismail, A, Yan, J & Shen, J 2011, 'Analyzing fault-impact region of composite service for supporting fault handling process', Proceedings - 2011 IEEE International Conference on Services Computing, SCC 2011, pp. 290-297.View/Download from: Publisher's site
A fault situation occurs to a service needs to be well analyzed and handled in order to ensure the reliability of composite service. The analysis can be driven by understanding the impact caused by the faulty service on the other services as well as the entire composition. Existing works have given less attention to this issue, in particular, the temporal impact situation caused by the fault. Thus, we propose an approach to analyzing the temporal impact and generating the impact region. The region can be utilized by the handling mechanism to prioritize the services to be repaired. The approach begins by estimating the updated temporal behavior of the composite service after the fault situation occurs, followed by identifying the potential candidates of the impact region. The concept of temporal negative impact is introduced to support the identification activity. Intuitively, the approach can assist in reducing the number of service changes in handling the fault situation. © 2011 IEEE.
Shen, J, Beydoun, G, Yuan, S & Low, G 2011, 'Comparison of bio-inspired algorithms for peer selection in services composition', Proceedings - 2011 IEEE International Conference on Services Computing, SCC 2011, IEEE International Conference on Services Computing, IEEE, Washington, DC, USA, pp. 250-257.View/Download from: UTS OPUS or Publisher's site
One of the challenges for the P2P-based service composition process is how to effectively discover and select the most appropriate peers to execute the service applications when considering multiple properties of the requested services. Different ontology-based e-service profiles have been proposed to facilitate handling multiple properties and to enhance the service oriented process in order to achieve the total or partial automation of service discovery, selection and composition. This paper investigates how the ACO (Ant Colony Optimisation) algorithm and the GA (Genetic Algorithm) may facilitate P2P-based (Peer-to-Peer) service selection with multiple service properties. The performance of both algorithms is evaluated and compared statistically using a pooled t-test for 30 randomly generated composition scenarios. Our experimental results show that both algorithms can improve the quality of service composition, while showing that the ACO approach is the more effective. © 2011 IEEE.
Sun, Z, Shen, J & Yong, J 2011, 'DeDu: Building a deduplication storage system over cloud computing', Proceedings of the 2011 15th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2011, pp. 348-355.View/Download from: Publisher's site
This paper presents a deduplication storage system over cloud computing. Our deduplication storage system consists of two major components, a front-end deduplication application and Hadoop Distributed File System. Hadoop Distributed File System is common back-end distribution file system, which is used with a Hadoop database. We use Hadoop Distributed File System to build up a mass storage system and use a Hadoop database to build up a fast indexing system. With the deduplication applications, a scalable and parallel deduplicated cloud storage system can be effectively built up. We further use VMware to generate a simulated cloud environment. The simulation results demonstrate that our deduplication cloud storage system is more efficient than traditional deduplication approaches. © 2011 IEEE.
Al-Hmouz, A, Shen, J, Yan, J & Al-Hmouz, R 2010, 'Enhanced learner model for adaptive mobile learning', iiWAS2010 - 12th International Conference on Information Integration and Web-Based Applications and Services, pp. 783-786.View/Download from: Publisher's site
Personalisation and learner modelling are becoming more important in the area of mobile learning applications, taking into consideration learners' interests, preferences and contextual information. Students nowadays are able to learn anywhere and at any time. Mobile learning application content is one of several factors within various contexts that play an important role in the success of the adaptation process. The vast amount of data involved in any successful adaptation process creates complexity and poses serious challenges. This paper focuses on how to model the learner and all possible contexts in an extensible way that can be used for personalisation in mobile learning. The enhanced learner modelling structure to be used in a mobile learning system is proposed. The proposed structure provides per-sonalisation by adopting a hybrid approach combining two machine learning techniques. Copyright 2010 ACM.
Dillon, T, Shen, J, Mueller, G, Kim, SD, Lin, KJ & Venkatasubramanian, N 2010, 'Message from chairs', Proceedings - 2010 IEEE International Conference on Service-Oriented Computing and Applications, SOCA 2010.View/Download from: Publisher's site
Al-Hmouz, A, Shen, J & Yan, J 2009, 'A Machine Learning Based Framework for Adaptive Mobile Learning', ADVANCES IN WEB BASED LEARNING - ICWL 2009, 8th International Conference on Web Based Learning (ICWL 2009), SPRINGER-VERLAG BERLIN, Aachen, GERMANY, pp. 34-43.
Ismail, A, Yan, J & Shen, J 2009, 'Dynamic Service Selection for Service Composition with Time Constraints', ASWEC 2009: 20TH AUSTRALIAN SOFTWARE ENGINEERING CONFERENCE, PROCEEDINGS, 20th Australian Software Engineering Conference 2009, IEEE COMPUTER SOC, Gold Coast, AUSTRALIA, pp. 183-190.View/Download from: Publisher's site
Ismail, A, Yan, J & Shen, J 2009, 'Towards dynamic formation of temporal constraints for the service level agreements negotiation', IEEE International Conference on Service-Oriented Computing and Applications, SOCA' 09, pp. 72-79.View/Download from: Publisher's site
SLAs play an important role for the QoS-driven service composition. Meanwhile, the temporal constraints are one of the main elements in the management of SLA especially in specifying the validity period of the QoS offers. In practice, the temporal constraints should be generated dynamically by taking the resource capability of the provider into account. The generation should consider various parameters that influence the resource capability such as the expected duration of the required Web service, the amount of current utilization, the amount of available resources, the number of required time slots, etc. Therefore, this paper aims to elaborate this issue and present a temporal constraints formation for SLA negotiation framework. This framework is proposed in the context of service selection and SLA negotiation. It provides the foundation towards the dynamic formation. This paper also demonstrates the initial approach of temporal constraints formation. ©2009 IEEE.
Ismail, A, Yan, J & Shen, J 2009, 'Verification of Composite Services with Temporal Consistency Checking and Temporal Satisfaction Estimation', WEB INFORMATION SYSTEMS ENGINEERING - WISE 2009, PROCEEDINGS, 10th International Conference on Web Information Systems Engineering (WISE 2009), SPRINGER-VERLAG BERLIN, Poznan, POLAND, pp. 343-350.
Shen, J & Yuan, S 2009, 'QoS-Aware Peer Services Selection Using Ant Colony Optimisation', BUSINESS INFORMATION SYSTEMS WORKSHOPS, 12th International Conference on Business Information Systems, SPRINGER-VERLAG BERLIN, Poznan, POLAND, pp. 362-374.
Shen, J, Yuan, S & Krishna, A 2008, 'Dynamic Selection of Service Peers with Multiple Property Specifications', BUSINESS PROCESS MANAGEMENT WORKSHOPS, Business Process Management Workshops, SPRINGER-VERLAG BERLIN, Milan, ITALY, pp. 609-+.
Shi, X-P, Shen, J & Wang, L 2009, 'Research and Its Implementation of A Remote Teaching Application System Model Based on Self-organization Components', PROCEEDINGS OF THE FIRST INTERNATIONAL WORKSHOP ON EDUCATION TECHNOLOGY AND COMPUTER SCIENCE, VOL II, 1st International Workshop on Education Technology and Computer Science, IEEE COMPUTER SOC, Wuhan, PEOPLES R CHINA, pp. 444-+.View/Download from: Publisher's site
Xu, J, Xiao, G, Lu, JW, Liang, Q & Shen, J 2009, 'Customizable Data Exchange based on Web Service', ICEBE 2009: IEEE INTERNATIONAL CONFERENCE ON E-BUSINESS ENGINEERING, PROCEEDINGS, IEEE International Conference on e-Business Engineering, IEEE COMPUTER SOC, Macau, PEOPLES R CHINA, pp. 522-+.View/Download from: Publisher's site
Yuan, S, Shen, J & Krishna, A 2009, 'Ant Inspired Scalable Peer Selection in Ontology-Based Service Composition', 2009 WORLD CONFERENCE ON SERVICES PART, World Conference on Services Part II (SERVICES PART-2), IEEE, San Francisco, CA, pp. 95-+.View/Download from: Publisher's site
Shen, J & Yuan, S 2008, 'Adaptive Task Allocation for P2P-Based e-Services Composition', 2008 3RD INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND APPLICATIONS, VOLS 1 AND 2, 3rd International Conference on Pervasive Computing and Applications, IEEE, Alexandria, EGYPT, pp. 313-318.View/Download from: Publisher's site
Shen, J & Yuan, S 2008, 'Modelling quality and spatial characteristics for autonomous e-service peers', CEUR Workshop Proceedings, pp. 49-52.
In this paper, we present an autonomous and scalable WSMO-based methodology to describe quality of service (QoS) and geographic features of e-services in a peer-to-peer based environment. To fully explore the usability of service mining and categorisation, we designed an algorithm to select the most appropriate peers to improve effective service composition.
Shen, J, Krishna, A, Yuan, S, Cai, K & Qin, Y 2008, 'A pragmatic GIS-oriented ontology for location based services', Proceedings of the Australian Software Engineering Conference, ASWEC, pp. 562-569.View/Download from: Publisher's site
With advances in automatic position sensing and wireless connectivity, location-based services (LBS) are rapidly developing, particularly in fields of geographic, tourism and logistic information systems. Currently, Web service has been viewed as one of most significant innovations in business industry, and designed on demand to provide spatial related information for LBS consumption. However, the traditional Web Service Description Language (WSDL) cannot meet those requirements, as WSDL is not able to support semantic content and information. In recent years, Ontology came up with an effective approach to enhance service description, automated discovery, dynamic composition, enactment, and other tasks such as managing and using service-based systems. In this paper, we propose geographic ontology based on Geography Markup Language (GML) and extend OWL-S profile to form geographic profile. Web service, which is advertised on the basis of our GeoProfile, contains geographic information inherently. © 2008 IEEE.
Shen, J, Krishna, A, Yuan, S, Cai, K & Qin, Y 2008, 'A pragmatic GIS-oriented ontology for location based services', ASWEC 2008: 19TH AUSTRALIAN SOFTWARE ENGINEERING CONFERENCE, PROCEEDINGS, 19th Australian Software Engineering Conference, IEEE COMPUTER SOC, Perth, AUSTRALIA, pp. 562-+.View/Download from: Publisher's site
Yuan, S, Shen, J & Yan, J 2008, 'A Practical Geographic Ontology for Spatial Web Services', 2008 IEEE INTERNATIONAL CONFERENCE ON SERVICES COMPUTING, PROCEEDINGS, VOL 2, IEEE International Conference on Services Computing, IEEE COMPUTER SOC, Honolulu, HI, pp. 579-580.View/Download from: Publisher's site
Aslam, MA, Shen, J, Auer, S & Herrmann, M 2007, 'An integration life cycle for semantic Web services composition', PROCEEDINGS OF THE 2007 11TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN, VOLS 1 AND 2, 11th International Conference on Computer Supported Cooperative Work in Design, IEEE, Melbourne, AUSTRALIA, pp. 490-+.
Yuan, S & Shen, J 2007, 'QoS-aware service selection in P2P-based business process frameworks', 9TH IEEE INTERNATIONAL CONFERENCE ON E-COMMERCE TECHNOLOGY/4TH IEEE INTERNATIONAL CONFERENCE ON ENTERPRISE COMPUTING, E-COMMERCE AND E-SERVICES, 9th IEEE International Conference on E-Commerce Technology/4th IEEE International Conference on Enterprise Computing, E-Commerce and E-Services, IEEE COMPUTER SOC, Tokyo, JAPAN, pp. 675-+.View/Download from: Publisher's site
Aslam, MA, Auer, S, Shen, J & Herrmann, M 2006, 'Expressing business process models as OWL-S ontologies', BUSINESS PROCESS MANAGEMENT WORKSHOPS, 4th International Conference on Business Process Management, SPRINGER-VERLAG BERLIN, Vienna, AUSTRIA, pp. 400-415.
Shen, J, Yan, J & Yang, Y 2006, 'SwinDeW-S: Extending P2P workflow systems for adaptive composite web services', 2006 AUSTRALIAN SOFTWARE ENGINEERING CONFERENCE, PROCEEDINGS, 17th Australian Software Engineering Conference (ASWEC 2006), IEEE COMPUTER SOC, Sydney, AUSTRALIA, pp. 61-+.
Shen, J, Yang, Y & Yan, J 2005, 'Adapting P2P based decentralised workflow system SwinDeW-S with web service profile support', PROCEEDINGS OF THE NINTH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN, VOLS 1 AND 2, 9th International Conference on Computer Supported Cooperative Work in Design, COVENTRY UNIV, Coventry, ENGLAND, pp. 535-540.View/Download from: Publisher's site
Shen, J, Yang, Y, Zhu, C & Wan, CG 2005, 'From BPEL4WS to OWL-S: Integrating e-business process descriptions', 2005 IEEE International Conference on Services Computing, Vol 1, Proceedings, IEEE International Conference on Services Computing, IEEE COMPUTER SOC, Orlando, FL, pp. 181-188.
Shen, J, Yang, Y & Lalwani, B 2004, 'Mapping web services specifications to process ontology: Opportunities and limitations', 10TH IEEE INTERNATIONAL WORKSHOP ON FUTURE TRENDS OF DISTRIBUTED COMPUTING SYSTEMS, PROCEEDINGS, 10th IEEE International Workshop on Future Trends of Distributed Computing Systems (FTDCS 2004), IEEE COMPUTER SOC, Suzhou, PEOPLES R CHINA, pp. 229-235.
Jun, S & Yun, Y 2003, 'RDF-based knowledge models for network management', INTEGRATED NETWORK MANAGEMENT VIII, 8th International Symposium on Integrated Network Management (IM 2003), KLUWER ACADEMIC PUBLISHERS, COLORADO SPRINGS, CO, pp. 123-126.View/Download from: Publisher's site
López de Vergara, JE, Villagrá, VA, Berrocal, J, Asensio, JI & Pignaton, R 2003, 'Semantic management: Application of ontologies for the integration of management information models', IFIP Advances in Information and Communication Technology, pp. 131-134.View/Download from: Publisher's site
The multiplicity of Network Management models (SNMP, CMIP, DMI, WBEM...) has raised the need of defining multiple mechanisms to allow the interoperability among all involved management domains. One basic component of such interoperability is the mapping between the information models that each domain specifies. These mappings, usually carried out with syntactical translations, can reach the semantic level by using ontologies. This article shows the advantages of using formal ontology techniques to improve the integration of current network management models. © 2003 by Springer Science+Business Media Dordrecht.
Shen, J, Yang, Y & Luo, JZ 2002, 'A Petri net model for session services', ENGINEERING AND DEPLOYMENT OF COOPERATIVE INFORMATION SYSTEMS, PROCEEDINGS, 1st International Conference on Engineering and Deployment of Cooperative Information Systems, SPRINGER-VERLAG BERLIN, BEIJING, PEOPLES R CHINA, pp. 303-314.
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