Taskification – Gamification of Tasks

Book chapter

Naeem, U., Islam, S., Sharif, M., Sudakov, Sergey and Azam, Awais 2017. Taskification – Gamification of Tasks. in: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers Association for Computing Machinery (ACM). pp. 631-634
AuthorsNaeem, U., Islam, S., Sharif, M., Sudakov, Sergey and Azam, Awais
Abstract

Leading a busy lifestyle can have a negative impact on the productivity levels of individuals. Lack of motivation is also another factor that can influence the output of any task or activity conducted by a user. This also applies to students within an academic context, where the distractions and lack of motivation can have a negative impact on their learning and results. In this paper, we propose ‘Taskification’, a task management mobile application, which incorporates core gamification features. The objective of this application is to increase student engagement and motivation during tasks such as coursework or exam preparation.

Book titleProceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers
Page range631-634
Year2017
PublisherAssociation for Computing Machinery (ACM)
Publication dates
Print11 Sep 2017
Publication process dates
Deposited11 Sep 2017
EventUbiComp/ISWC'17 Adjunct SmartGuidance Conference, 2017
ISBN978-1-4503-5190-4
Digital Object Identifier (DOI)https://doi.org/10.1145/3123024.3124423
Web address (URL)https://doi.org/10.1145/3123024.3124423
Accepted author manuscript
License
CC BY
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Okoye, K., Islam, S., Naeem, U. and Sharif, S. 2020. Semantic-Based Process Mining Technique for Annotation and Modelling of Domain Processes. International Journal of Innovative Computing, Information and Control. 16 (3), pp. 899-921. https://doi.org/10.24507/ijicic.16.03.899
Positron emission tomography PET/CT harmonisation study of different clinical PET/CT scanners using commercially available software
Lowe, G., Spottiswoode, B., Declerck, J., Sullivan,, K., Sharif, S., Wong, W. and Sanghera, B. 2020. Positron emission tomography PET/CT harmonisation study of different clinical PET/CT scanners using commercially available software. BJR Open. 2 (Art. 20190035). https://doi.org/10.1259/bjro.20190035
An Accurate Ensemble Classifier for Medical Volume Analysis: Phantom and Clinical PET Study
Sharif, S., Abbod, M., Al-Bayatti, A., Amira, A., Alfakeeh, A. and Sanghera, B. 2020. An Accurate Ensemble Classifier for Medical Volume Analysis: Phantom and Clinical PET Study. IEEE Access. 8, pp. 37482-37494. https://doi.org/10.1109/ACCESS.2020.2975135
Variance Ranking for Multi-Classed Imbalanced Datasets: A Case Study of One-Versus-All
Ebenuwa, S., Sharif, S., Al-Nemrat, A., Al-Bayatti, A. H., Alalwan, N., Alzahrani, A. I. and Alfarraj, O. 2019. Variance Ranking for Multi-Classed Imbalanced Datasets: A Case Study of One-Versus-All. Symmetry. 11 (Art. 1504). https://doi.org/10.3390/sym11121504
Policy-Based Security Management System for 5G Heterogeneous Networks
Alquhayz, H., Alalwan, N., Alzahrani, A. I., Al-Bayatti, A. H. and Sharif, S. 2019. Policy-Based Security Management System for 5G Heterogeneous Networks. Wireless Communications and Mobile Computing. 2019 (Art. 4582391). https://doi.org/10.1155/2019/4582391
A Framework for Augmented Reality Based Shared Experiences
Ali, A., Glackin, C., Cannings, N., Wall, J., Sharif, S. and Moniri, M. 2019. A Framework for Augmented Reality Based Shared Experiences. Immersive Learning Research Network - iLRN. London, UK 23 - 27 Jun 2019 Technischen Universität Graz. https://doi.org/10.3217/978-3-85125-657-4-24
Improving Student Engagement and Performance in Computing Final Year Projects
Naeem, U., Islam, S. and Siddiqui, A. 2019. Improving Student Engagement and Performance in Computing Final Year Projects. IEEE TALE 2019. Yogyakarta - Indonesia 10 - 13 Oct 2019 IEEE. https://doi.org/10.1109/TALE48000.2019.9225860
A Deep Learning Based Suggested Model to Detect Necrotising Enterocolitis in Abdominal Radiography Images
Van Druten, J., Sharif, S., Chan, S. S., Chong, C. and Abdalla, H. 2019. A Deep Learning Based Suggested Model to Detect Necrotising Enterocolitis in Abdominal Radiography Images. IEEE International Conference on Computing, Electronics & Communications Engineering 2019 (IEEE iCCECE '19) . London Metropolitan University, London, UK 22 - 23 Aug 2019 IEEE. https://doi.org/10.1109/iCCECE46942.2019.8941615
Context-Aware Driver Distraction Severity Classification using LSTM Network
Fasanmade, A., Aliyu, S., He, Y., Al-Bayatti, A. H., Sharif, S. and Alfakeeh, A. S. 2019. Context-Aware Driver Distraction Severity Classification using LSTM Network. IEEE International Conference on Computing, Electronics & Communications Engineering 2019 (IEEE iCCECE '19) . London Metropolitan University, London, UK 22 - 23 Aug 2019 IEEE. pp. 147-152 https://doi.org/10.1109/iCCECE46942.2019.8941966
Predicting the Standard and Deviant Patterns In EEG Signals Based On Deep Learning Model
Sharif, S., Al-Bayatti, A. H. and Alfakeeh, A. S. 2019. Predicting the Standard and Deviant Patterns In EEG Signals Based On Deep Learning Model. IEEE International Conference on Computing, Electronics & Communications Engineering 2019 (IEEE iCCECE '19) . London Metropolitan University, London, UK 22 - 23 Aug 2019 IEEE. https://doi.org/10.1109/iCCECE46942.2019.8941730
Effect of PET Image Reconstruction Techniques on Unexpected Aorta Uptake
Hirji, H., Sullivan, K., Lasker, I., Sharif, S., Nunes, A., Shepherd, C., Wong, W. and Sanghera, B. 2019. Effect of PET Image Reconstruction Techniques on Unexpected Aorta Uptake. Molecular Imaging and Radionuclide Therapy. 28 (1), pp. 1-7. https://doi.org/10.4274/mirt.galenos.2018.88528
Variance Ranking Attributes Selection Techniques for Binary Classification Problem in Imbalance Data
Ebenuwa, S., Sharif, M., Alazab, Mamoun and Al-Nemrat, A. 2019. Variance Ranking Attributes Selection Techniques for Binary Classification Problem in Imbalance Data. IEEE Access. 7, pp. 24649-24666. https://doi.org/10.1109/ACCESS.2019.2899578
Tracking Functional Decline using Ambient Intelligence for Alzheimer's Patients
Lee, Sin Wee, Naeem, U., Anthony, Richard, Tawil, A., Azam, Muhammad Awais and Preston, David 2014. Tracking Functional Decline using Ambient Intelligence for Alzheimer's Patients. in: Dogru, Ali H. and Suh, Sang (ed.) Proceedings of the 19th International Conference on Transformative Science and Engineering, Business and Social Innovation Society for Design and Process Science. pp. 107-116
Inference of Activities with Unexpected Actions Using Pattern Mining
Nasreen, Shamila, Azam, Muhammad Awais, Naeem, U. and Ghazanfar, Mustansar Ali 2015. Inference of Activities with Unexpected Actions Using Pattern Mining. in: UbiComp/ISWC'15 Adjunct: Adjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers Association for Computing Machinery (ACM). pp. 1479-1488
Inference of Hygiene Behaviours While Recognising Activities of Daily Living
Naeem, U., Tawil, Abdel-Rahman, Semelis, Ivans, Judah, Gaby and Aunger, Robert 2015. Inference of Hygiene Behaviours While Recognising Activities of Daily Living. in: Mansoor, Wathiq, Maamar, Zakaria and Rabhi, Fethi (ed.) ICCASA '14: Proceedings of the 3rd International Conference on Context-Aware Systems and Applications ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering). pp. 154-161
Medical data analysis based on Nao robot: An automated approach towards robotic real-time interaction with human body
Sharif, M. and Alsibai, Mohammed Hayyan 2018. Medical data analysis based on Nao robot: An automated approach towards robotic real-time interaction with human body. in: 2017 7th IEEE International Conference on Control System, Computing and Engineering (ICCSCE) IEEE. pp. 91-96
A Proposed Machine Learning Based Collective Disease Model to Enable Predictive Diagnostics in Necrotising Enterocolitis
van Druten, Jacqueline, Sharif, M., Khashu, Minesh and Abdalla, H. 2019. A Proposed Machine Learning Based Collective Disease Model to Enable Predictive Diagnostics in Necrotising Enterocolitis. in: Miraz, Mahdi H., Exce, Peter S., Jones, Andrew, Soomro, Safeeullah and Ali, Maaruf (ed.) Proceedings 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE) IEEE. pp. 101-106
A Machine Learning Techniques to Detect Counterfeit Medicine Based on X-Ray Fluorescence Analyser
Alsallal, Muna, Sharif, M., Al-Ghzawi, Baydaa and al Mutoki, Sabah Mohammed Mlkat 2019. A Machine Learning Techniques to Detect Counterfeit Medicine Based on X-Ray Fluorescence Analyser. in: Miraz, Mahdi H., Excell, Peter S., Jones, Andrew, Soomro, Safeeullah and Ali, Maaruf (ed.) Proceedings 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE) IEEE. pp. 118-122
Neural Predictors of Gait Stability When Walking Freely in the Real-World.
Pizzamiglio, S., Abdalla, H., Naeem, U. and Turner, D. 2018. Neural Predictors of Gait Stability When Walking Freely in the Real-World. Journal of NeuroEngineering and Rehabilitation. 15 (11). https://doi.org/10.1186/s12984-018-0357-z
An Innovative EPW Design Using Add-on Features to Meet Malaysian Requirements
Alsibai, Mohammed Hayyan, Sharif, M., Yaakub, Salma and Hamran, Nurul Nadia Nor 2018. An Innovative EPW Design Using Add-on Features to Meet Malaysian Requirements. in: Proceedings of the 7th IEEE International Conference on Control Systems, Computing and Engineering (ICCSCE 2017) IEEE. pp. 180-185
An Effective TeleHealth Assistive System to Support Senior Citizen at Home or Care-Homes
Sharif, M., Alsallal, Muna and Herghelegiu, Lucian 2018. An Effective TeleHealth Assistive System to Support Senior Citizen at Home or Care-Homes. IEEE International Conference on Computing, Electronics & Communications Engineering 2018 (iCCECE '18). Southend, UK 16 - 17 Aug 2018 IEEE. pp. 113-117 https://doi.org/10.1109/iCCECOME.2018.8658877
Functional Connectivity Evaluation for Infant EEG Signals based on Artificial Neural Network
Sharif, M., Naeem, U., Islam, S. and Karami, A. 2018. Functional Connectivity Evaluation for Infant EEG Signals based on Artificial Neural Network. Arai, Kohei, Kapoor, Supriya and Bhatia, Rahul (ed.) Intelligent Systems Conference (IntelliSys) 2018. London, UK 06 - 07 Sep 2018 Springer, Cham. https://doi.org/10.1007/978-3-030-01057-7_34
The Application of a Semantic-Based Process Mining Framework on a Learning Process Domain
Okoye, Kingsley, Islam, S., Naeem, U., Sharif, M., Azam, Muhammad Awais and Karami, A. 2018. The Application of a Semantic-Based Process Mining Framework on a Learning Process Domain. Arai, Kohei, Kapoor, Supriya and Bhatia, Rahul (ed.) Intelligent Systems Conference (IntelliSys) 2018. London, UK 06 - 07 Sep 2018 Springer, Cham. https://doi.org/10.1007/978-3-030-01054-6_96
Authentication of Smartphone Users Based on Activity Recognition and Mobile Sensing
Ehatisham-ul-Haq, Muhammad, Azam, Muhammad Awais, Loo, Jonathan, Shuang, Kai, Islam, S., Naeem, U. and Amin, Yasar 2017. Authentication of Smartphone Users Based on Activity Recognition and Mobile Sensing. Sensors. 17 (9), p. 2043. https://doi.org/10.3390/s17092043
Identifying Smartphone Users based on their Activity Patterns via Mobile Sensing
Ehatisham-ul-Haq, M., Azam, Muhammad Awais, Naeem, U., Rѐhman, Shafiq Ur and Khalid, Asra 2017. Identifying Smartphone Users based on their Activity Patterns via Mobile Sensing. Procedia Computer Science. 113, pp. 202-209. https://doi.org/10.1016/j.procs.2017.08.349
SignalSense - Towards Quality Service
Islam, S., Sharif, M., Naeem, U. and Geehan, James 2017. SignalSense - Towards Quality Service. in: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers Association for Computing Machinery (ACM). pp. 627-630
CrimeSafe - Helping you stay safe
Islam, S., Naeem, U., Sharif, M. and Dovnarovic, Arnold 2017. CrimeSafe - Helping you stay safe. in: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers Association for Computing Machinery (ACM). pp. 642-645
Neural correlates of single- and dual-task walking in the real world
Pizzamiglio, Sara, Naeem, U., Abdalla, H. and Turner, D. 2017. Neural correlates of single- and dual-task walking in the real world. Frontiers in Human Neuroscience. 11, p. Art 460. https://doi.org/10.3389/fnhum.2017.00460
The Future of Enterprise Security with Regards to Mobile Technology and Applications
Tagoe, F. T. and Sharif, M. 2017. The Future of Enterprise Security with Regards to Mobile Technology and Applications. in: Jahankhani, Hamid, Carlile, Alex, Emm, David, Hosseinian-Far, Amin, Brown, Guy, Sexton, Graham and Jamal, Arshad (ed.) Global Security, Safety and Sustainability - The Security Challenges of the Connected World. ICGS3 2017 Proceedings Springer International Publishing.
Actor-Network Theory as a Framework to Analyse Technology Acceptance Model’s External Variables: The Case of Autonomous Vehicles
Seuwou, Patrice, Banissi, Ebad, Ubakanma, George, Sharif, M. and Healey, Ann 2017. Actor-Network Theory as a Framework to Analyse Technology Acceptance Model’s External Variables: The Case of Autonomous Vehicles. in: Jahankhani, Hamid, Carlile, Alex, Emm, David, Hosseinian-Far, Amin, Brown, Guy, Sexton, Graham and Jamal, Arshad (ed.) Global Security, Safety and Sustainability - The Security Challenges of the Connected World. ICGS3 2017 Proceedings Springer International Publishing.
Recognizing activities of daily living from patterns and extraction of web knowledge
Ihianle, I., Naeem, U., Tawil, A. and Azam, Muhammad Awais 2016. Recognizing activities of daily living from patterns and extraction of web knowledge. in: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct - UbiComp '16 New York, NY, USA Association for Computing Machinery (ACM). pp. 1255-1262
Using semantic-based approach to manage perspectives of process mining: Application on improving learning process domain data
Kingsley, Okoye, Tawil, Abdel-Rahman H., Naeem, U., Islam, S. and Lamine, Elyes 2017. Using semantic-based approach to manage perspectives of process mining: Application on improving learning process domain data. in: 2016 IEEE International Conference on Big Data (Big Data) IEEE. pp. 3529-3538
Inference Engine Based on a Hierarchical Structure for Detecting Everyday Activities within the Home
Naeem, U., Tawil, A., Semelis, Ivans, Azam, Muhammad Awais and Ghazanfar, Mustansar Ali 2017. Inference Engine Based on a Hierarchical Structure for Detecting Everyday Activities within the Home. in: Bi, Yaxin, Kapoor, Supriya and Bhatia, Rahul (ed.) Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016 Springer, Cham. pp. 969-986
Integration operators for generating RDF/OWL-based user defined mediator views in a grid environment
Tawil, Abdel-Rahman H., Taweel, Adel, Naeem, U., Montebello, Matthew, Bashroush, R. and Al-Nemrat, A. 2014. Integration operators for generating RDF/OWL-based user defined mediator views in a grid environment. Journal of Intelligent Information Systems. 43 (1), pp. 1-32. https://doi.org/10.1007/s10844-013-0300-5
A Semantic Reasoning Method Towards Ontological Model for Automated Learning Analysis
Okoye, Kingsley, Tawil, A., Naeem, U. and Lamine, Elyes 2015. A Semantic Reasoning Method Towards Ontological Model for Automated Learning Analysis. in: Pillay, Nelishia, Engelbrecht, Andries P., Abraham, Ajith, Plessis, Mathys C. du, Snášel, Václav and Muda, Azah Kamilah (ed.) Advances in Nature and Biologically Inspired Computing Cham, Switzerland Springer International Publishing.
A dynamic segmentation based activity discovery through topic modelling
Kennedy, Ihianle Isibor, Naeem, U. and Tawil, A. 2016. A dynamic segmentation based activity discovery through topic modelling. in: IET International Conference on Technologies for Active and Assisted Living (TechAAL) IEEE.
An efficient system for preprocessing confocal corneal images for subsequent analysis
Sharif, M., Qahwaji, Rami, Hayajneh, Sofyan, Ipson, Stanley, Alzubaidi, Rania and Brahma, Arun 2014. An efficient system for preprocessing confocal corneal images for subsequent analysis. in: 2014 14th UK Workshop on Computational Intelligence (UKCI) IEEE.
Dependence Cluster Visualization
Islam, S., Krinke, Jens and Binkley, David 2010. Dependence Cluster Visualization. in: Proceedings of the 5th international symposium on Software visualization New York, NY, USA Association for Computing Machinery (ACM). pp. 93-102
Artificial Neural Network-Based System for PET Volume Segmentation
Sharif, M., Abbod, Maysam, Amira, Abbes and Zaidi, Habib 2010. Artificial Neural Network-Based System for PET Volume Segmentation. International Journal of Biomedical Imaging. 2010 (105610). https://doi.org/10.1155/2010/105610
Artificial Neural Network-Statistical Approach for PET Volume Analysis and Classification
Sharif, M., Abbod, Maysam, Amira, Abbes and Zaidi, Habib 2012. Artificial Neural Network-Statistical Approach for PET Volume Analysis and Classification. Advances in Fuzzy Systems. 2012 (327861). https://doi.org/10.1155/2012/327861
Machine Learning Optimisation for Realistic 2D and 3D PET-CT Phantom Study
Sharif, M., Abbod, Maysam, Sonoda, Luke I. and Sanghera, Bal 2013. Machine Learning Optimisation for Realistic 2D and 3D PET-CT Phantom Study. British Journal of Applied Science & Technology. 4 (4), pp. 634-649. https://doi.org/10.9734/bjast/2014/5084
Preparation of 2D sequences of corneal images for 3D model building
Elbita, Abdulhakim, Qahwaji, Rami, Ipson, Stanley, Sharif, M. and Ghanchi, Faruque 2015. Preparation of 2D sequences of corneal images for 3D model building. Computer Methods and Programs in Biomedicine. 114 (2), pp. 194-205. https://doi.org/10.1016/j.cmpb.2014.01.009
Medical image classification based on artificial intelligence approaches: A practical study on normal and abnormal confocal corneal images
Sharif, M., Qahwaji, R., Ipson, S. and Brahma, A. 2015. Medical image classification based on artificial intelligence approaches: A practical study on normal and abnormal confocal corneal images. Applied Soft Computing. 36 (Nov.), pp. 269-282. https://doi.org/10.1016/j.asoc.2015.07.019
An efficient intelligent analysis system for confocal corneal endothelium images
Sharif, M., Qahwaji, R., Shahamatnia, E., Alzubaidi, R., Ipson, S. and Brahma, A. 2015. An efficient intelligent analysis system for confocal corneal endothelium images. Computer Methods and Programs in Biomedicine. 122 (3), pp. 421-436. https://doi.org/10.1016/j.cmpb.2015.09.003
In Vivo Confocal Microscopic Corneal Images in health and disease with an emphasis on extracting features and visual signatures for corneal diseases: A review study
Alzubaidi, Rania, Sharif, M., Qahwaji, Rami, Ipson, Stanley and Brahma, Arun 2015. In Vivo Confocal Microscopic Corneal Images in health and disease with an emphasis on extracting features and visual signatures for corneal diseases: A review study. British Journal of Ophthalmology. 100 (1), pp. 41-55. https://doi.org/10.1136/bjophthalmol-2015-306934
Less is more: Temporal fault predictive performance over multiple Hadoop releases
Harman, Mark, Islam, S., Jia, Yue, Minku, Leandro L., Sarro, Federica and Srivisut, Komsan 2014. Less is more: Temporal fault predictive performance over multiple Hadoop releases. in: Goues, Claire Le and Yoo, Shin (ed.) Search-Based Software Engineering Springer International Publishing.
ORBS: Language-Independent Program Slicing
Binkley, David, Gold, Nicolas, Harman, Mark, Islam, S., Krinke, Jens and Yoo, Shin 2014. ORBS: Language-Independent Program Slicing. in: Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering New York, NY, USA Association for Computing Machinery (ACM). pp. 109-120
Jolinar: Analysing the Energy Footprint of Software Applications (demo)
Noureddine, A., Islam, S. and Bashroush, R. 2016. Jolinar: Analysing the Energy Footprint of Software Applications (demo). in: Proceedings of the 25th International Symposium on Software Testing and Analysis New York, NY, USA Association for Computing Machinery (ACM). pp. 445-448
Semantic-Based Model Analysis Towards Enhancing Information Values of Process Mining: Case Study of Learning Process Domain
Okoye, Kingsley, Tawila, Abdel-Rahman H., Naeem, U., Islam, S. and Lamine, Elyes 2017. Semantic-Based Model Analysis Towards Enhancing Information Values of Process Mining: Case Study of Learning Process Domain. in: Abraham, Ajith, Cherukuri, Aswani Kumar, Madureira, Ana Maria and Muda, Azah Kamilah (ed.) Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016) Springer, Cham.
Assessing the impact of global variables on program dependence and dependence clusters
Binkley, David, Harman, Mark, Hassoun, Youssef, Islam, S. and Li, Zheng 2009. Assessing the impact of global variables on program dependence and dependence clusters. Journal of Systems and Software. 83 (1), pp. 96-107. https://doi.org/10.1016/j.jss.2009.03.038
Requirements for the formal representation of pathophysiology mechanisms by clinicians
de Bono, B., Helvensteijn, M., Kokash, N., Martorelli, I., Sarwar, D., Islam, S., Grenon, P. and Hunter, P. 2016. Requirements for the formal representation of pathophysiology mechanisms by clinicians. Interface Focus. 6 (2), p. 20150075. https://doi.org/10.1098/rsfs.2015.0099
An empirical study on dependence clusters for effort-aware fault-proneness prediction
Yang, Yibiao, Harman, Mark, Krinke, Jens, Islam, S., Binkley, David, Zhou, Yuming and Xu, Baowen 2016. An empirical study on dependence clusters for effort-aware fault-proneness prediction. in: Lo, David, Apel, Sven and Khurshid, Sarfraz (ed.) ASE’16 Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering IEEE/ACM. pp. 296-307
Towards Cloud Security Monitoring: A Case Study
Ismail, Umar Mukhtar, Islam, S. and Islam, S. 2016. Towards Cloud Security Monitoring: A Case Study. in: 2016 Cybersecurity and Cyberforensics Conference (CCC) IEEE.
High-Frequency Intermuscular Coherence between Arm Muscles during Robot-Mediated Motor Adaptation
Pizzamiglio, Sara, De Lillo, Martina, Naeem, U., Abdalla, Hassan and Turner, D. 2017. High-Frequency Intermuscular Coherence between Arm Muscles during Robot-Mediated Motor Adaptation. Frontiers in Physiology. 7 (668), pp. 1-14. https://doi.org/10.3389/fphys.2016.00668
gUML: Reasoning about Energy at Design Time by Extending UML Deployment Diagrams with Data Centre Contextual Information
Jebraeil, Nigar, Noureddine, A., Doyle, J., Islam, S. and Bashroush, R. 2017. gUML: Reasoning about Energy at Design Time by Extending UML Deployment Diagrams with Data Centre Contextual Information. in: 2017 IEEE World Congress on Services (SERVICES) IEEE. pp. In Press
Cloud Strife: Expanding the Horizons of Cloud Gaming Services
Doyle, J., Islam, S., Bashroush, R. and O'Mahony, Donal 2017. Cloud Strife: Expanding the Horizons of Cloud Gaming Services. in: 2017 IEEE World Congress on Services (SERVICES) IEEE.
A Mutlimodal Approach to Measure the Levels Distraction of Pedestrians using Mobile Sensing
Pizzamiglio, S., Naeem, U., ur Réhman, Shafiq, Sharif, M., Abdalla, H. and Turner, D. 2017. A Mutlimodal Approach to Measure the Levels Distraction of Pedestrians using Mobile Sensing. Procedia Computer Science. 113, pp. 89-96. https://doi.org/10.1016/j.procs.2017.08.297
Recognition of Activities of Daily Living from Topic Model
Ihianle, I., Naeem, U. and Tawil, A. 2016. Recognition of Activities of Daily Living from Topic Model. Procedia Computer Science. 98, pp. 24-31. https://doi.org/10.1016/j.procs.2016.09.007
Measuring energy footprint of software features
Islam, S., Noureddine, A. and Bashroush, Rabih 2016. Measuring energy footprint of software features. in: 2016 IEEE 24th International Conference on Program Comprehension (ICPC) IEEE.
PORBS: A parallel observation-based slicer
Islam, S. and Binkley, David 2016. PORBS: A parallel observation-based slicer. in: 2016 IEEE 24th International Conference on Program Comprehension (ICPC) IEEE.
Efficient Identification of Linchpin Vertices in Dependence Clusters
Binkley, David, Gold, Nicolas, Harman, Mark, Islam, S., Krinke, Jens and Li, Zheng 2013. Efficient Identification of Linchpin Vertices in Dependence Clusters. ACM Transactions on Programming Languages and Systems. 35 (2), pp. 1-35.
ORBS and the limits of static slicing
Binkley, David, Gold, Nicolas, Harman, Mark, Islam, S., Krinke, Jens and Yoo, Shin 2015. ORBS and the limits of static slicing. in: 2015 IEEE 15th International Working Conference on Source Code Analysis and Manipulation (SCAM) IEEE. pp. 1-10
Recognition Framework for Inferring Activities of Daily Living Based on Pattern Mining
Nasreen, Shamila, Azam, Muhammad Awais, Naeem, U., Ghazanfar, Mustansar Ali and Khalid, Asra 2016. Recognition Framework for Inferring Activities of Daily Living Based on Pattern Mining. Arabian Journal for Science and Engineering. 41 (8), pp. 3113-3126. https://doi.org/10.1007/s13369-016-2091-9
Coherent clusters in source code
Islam, S., Krinke, Jens, Binkley, David and Harman, Mark 2013. Coherent clusters in source code. Journal of Systems and Software. 88, pp. 1-24.
Uncovering Dependence Clusters and Linchpin Functions
Binkley, David, Beszédes, Árpád, Islam, S., Jász, Judit and Vancsics, Béla 2015. Uncovering Dependence Clusters and Linchpin Functions. in: 2015 IEEE 31st International Conference on Software Maintenance and Evolution (ICSME) IEEE. pp. 141-150
Activities of daily life recognition using process representation modelling to support intention analysis
Naeem, U., Bashroush, R., Anthony, Richard, Azam, Muhammad Awais, Tawil, Abdel Rahman, Lee, S. and Mou-Ling, Dennis 2015. Activities of daily life recognition using process representation modelling to support intention analysis. International Journal of Pervasive Computing and Communications. 11 (3), pp. 347-371. https://doi.org/10.1108/IJPCC-01-2015-0002
Novel centroid selection approaches for KMeans-clustering based recommender systems
Zahra, Sobia, Ghazanfar, Mustansar Ali, Khalid, Asra, Azam, Muhammad Awais, Naeem, U. and Prugel-Bennett, Adam 2015. Novel centroid selection approaches for KMeans-clustering based recommender systems. Information Sciences. 320, pp. 156-189.
Semantic Process Mining Towards Discovery and Enhancement of Learning Model Analysis
Okoye, Kingsley, Tawil, Abdel Rahman H., Naeem, U. and Lamine, Elyes 2015. Semantic Process Mining Towards Discovery and Enhancement of Learning Model Analysis. in: 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security, and 2015 IEEE 12th International Conference on Embedded Software and Systems IEEE. pp. 363-370
A Semantic Rule-based Approach Supported by Process Mining for Personalised Adaptive Learning
Okoye, Kingsley, Tawil, A., Naeem, U., Bashroush, Rabih and Lamine, Elyes 2014. A Semantic Rule-based Approach Supported by Process Mining for Personalised Adaptive Learning. Procedia Computer Science. 37, pp. 203-210.
Frequent Pattern Mining Algorithms for Finding Associated Frequent Patterns for Data Streams: A Survey
Nasreen, Shamila, Azam, Muhammad Awais, Shehzad, Khurram, Naeem, U. and Ghazanfar, Mustansar Ali 2014. Frequent Pattern Mining Algorithms for Finding Associated Frequent Patterns for Data Streams: A Survey. Procedia Computer Science. 37, pp. 109-116.
Statistical Sampling Approach to Investigate Child Pornography Cases
Sarantinos, N., Al-Nemrat, A. and Naeem, U. 2013. Statistical Sampling Approach to Investigate Child Pornography Cases. 2013 Fourth Cybercrime and Trustworthy Computing Workshop (CTC). Sydney NSW, Australia 21 - 22 Nov 2013 IEEE. https://doi.org/10.1109/CTC.2013.14
A Framework to Recognise Daily Life Activities with Wireless Proximity and Object Usage Data
Azam, M.A., Loo, J., Naeem, U., Khan, S.K.A., Lasebae, A. and Gemikonakli, O. 2012. A Framework to Recognise Daily Life Activities with Wireless Proximity and Object Usage Data. in: Proceedings of 23rd IEEE International Symposium on Personal, Indoor and Mobile Radio Communication 2012 IEEE. pp. 590-595
Behavioural Patterns Analysis of Low Entropy People Using Proximity Data
Azam, M.A., Loo, J., Khan, S.K.A., Naeem, U., Adeel, M. and Ejaz, Waleed 2012. Behavioural Patterns Analysis of Low Entropy People Using Proximity Data. Innovative Information Science & Technology Research Group.
A Comparison of Two Hidden Markov Approaches to Task Identification in the Home Environment
Naeem, U. and Bigham, John 2007. A Comparison of Two Hidden Markov Approaches to Task Identification in the Home Environment. Proceedings of the 2nd International Conference on Pervasive Computing and Applications, Birmingham, UK, 2007, pp. 383-388
Recognising Activities of Daily Life Using Hierarchical Plans
Naeem, U., Bigham, John and Wang, Jinfu 2007. Recognising Activities of Daily Life Using Hierarchical Plans. Proceedings of the 2nd European Conference on Smart Sensing and Context, LNCS 4793, Lake District, UK, 2007, pp. 175-189
A Hierarchal Approach to Activity Recognition in the Home Environment based on Object Usage
Naeem, U. and Bigham, John 2008. A Hierarchal Approach to Activity Recognition in the Home Environment based on Object Usage. Proceedings of the 2008 Networking and Electronic Commerce Research Conference (NAEC 2008), Lake Garda, Italy, 2008, pp. 48-54
Recognising Activities of Daily Life through the Usage of Everyday Objects around the Home
Naeem, U. and Bigham, John 2009. Recognising Activities of Daily Life through the Usage of Everyday Objects around the Home. Proceedings of the 3rd International Conference on Pervasive Computing Technologies for Healthcare. Technologies to Counter Cognitive Decline Workshop London
Activity Recognition using a Hierarchical Framework
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