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Wifi-based human activity recognition using Raspberry Pi. (2020)
Conference Proceeding
FORBES, G., MASSIE, S. and CRAW, S. 2020. Wifi-based human activity recognition using Raspberry Pi. In Alamaniotis, M. and Pan, S. (eds.) Proceedings of Institute of Electrical and Electronics Engineers (IEEE) 32nd Tools with artificial intelligence international conference 2020 (ICTAI 2020), 9-11 Nov 2020, [virtual conference]. Piscataway: IEEE [online], pages 722-730. Available from: https://doi.org/10.1109/ICTAI50040.2020.00115

Ambient, non-intrusive approaches to smart home health monitoring, while limited in capability, are preferred by residents. More intrusive methods of sensing, such as video and wearables, can offer richer data but at the cost of lower resident uptake... Read More about Wifi-based human activity recognition using Raspberry Pi..

An IoT based industry 4.0 architecture for integration of design and manufacturing systems. (2020)
Journal Article
ANBALAGAN, A. and MORENO-GARCIA, C.F. 2021. An IoT based industry 4.0 architecture for integration of design and manufacturing systems. Materials today: proceedings [online], 46(17): proceedings of 3rd International conference on materials, manufacturing and modelling 2021 (ICMMM 2021), 19-21 March 2021, [virtual conference], pages 7135-7142. Available from: https://doi.org/10.1016/j.matpr.2020.11.196

This paper proposes an Internet of Things (IoT) based 5-stage Industry 4.0 architecture to integrate the design and manufacturing systems in a Cyber Physical Environment (CPE). It considers the transfer of design and manufacturing systems data throug... Read More about An IoT based industry 4.0 architecture for integration of design and manufacturing systems..

Performance analysis of different loss function in face detection architectures. (2020)
Conference Proceeding
FERDOUS, R.H., ARIFEEN, M.M., EIKO, T.S. and AL MAMUN, S. 2020. Performance analysis of different loss function in face detection architectures. In Kaiser, M.S., Bandyopadhyay, A., Muhmad, M. and Ray, K. (eds.) Proceedings of International conference on trends in computational and cognitive engineering 2020 (TCCE-2020), 17-18 December 2020, Dhaka, Bangladesh. Singapore: Springer [online], 659-669. Available from: https://doi.org/10.1007/978-981-33-4673-4_54

Masked face detection is a challenging task due to the occlusions created by the masks. Recent studies show that deep learning models can achieve effective performance for not only occluded faces but also for unconstrained environments, illuminations... Read More about Performance analysis of different loss function in face detection architectures..

Identifying implicit vulnerabilities through personas as goal models. (2020)
Conference Proceeding
FAILY, S., IACOB, C., ALI, R. and KI-ARIES, D. 2020. Identifying implicit vulnerabilities through personas as goal models. In Katsikas, S., Cuppens, F., Cuppens, N., Lambrinoudakis, C., Kalloniatis, C., Mylopoulos, J., Antón, A., Gritzalis, S., Meng, W. and Furnell, S. (eds.) Computer security: ESORICS 2020 international workshops, CyberICPS, SECPRE, and ADIoT: revised selected papers from the 4th International workshop on security and privacy requirements engineering (SECPRE 2020), co-located with the 25th European symposium on research in computer security (ESORICS 2020), 14-18 September 2020, Guildford, UK. Lecture notes in computer science, 12501. Cham: Springer [online], pages 185-202. Available from: https://doi.org/10.1007/978-3-030-64330-0_12

When used in requirements processes and tools, personas have the potential to identify vulnerabilities resulting from misalignment between user expectations and system goals. Typically, however, this potential is unfulfilled as personas and system go... Read More about Identifying implicit vulnerabilities through personas as goal models..

A pipeline framework for robot maze navigation using computer vision, path planning and communication protocols. (2020)
Conference Proceeding
RODRIGUEZ-TIRADO, A., MAGALLAN-RAMIREZ, D., MARTINEZ-AGUILAR, J.D., MORENO-GARCIA, C.F., BALDERAS, D. and LOPEZ-CAUDANA, E. 2020. A pipeline framework for robot maze navigation using computer vision, path planning and communication protocols. In Proceedings of 13th Developments in eSystems engineering international conference 2020 (DeSe 2020), 13-17 December 2020, [virtual conference]. Piscataway: IEEE [online], pages 152-157. Available from: https://doi.org/10.1109/DeSE51703.2020.9450731

Maze navigation is a recurring challenge in robotics competitions, where the aim is to design a strategy for one or several entities to traverse the optimal path in a fast and efficient way. To do so, numerous alternatives exist, relying on different... Read More about A pipeline framework for robot maze navigation using computer vision, path planning and communication protocols..

Ensemble-based relationship discovery in relational databases. (2020)
Conference Proceeding
OGUNSEMI, A., MCCALL, J., KERN, M., LACROIX, B., CORSAR, D. and OWUSU, G. 2020. Ensemble-based relationship discovery in relational databases. In Bramer, M. and Ellis, R. (eds.) Artificial intelligence XXXVII: proceedings of 40th British Computer Society's Specialist Group on Artificial Intelligence (SGAI) Artificial intelligence international conference 2020 (AI-2020), 15-17 December 2020, [virtual conference]. Lecture notes in artificial intelligence, 12498. Cham: Springer [online], pages 286-300. Available from: https://doi.org/10.1007/978-3-030-63799-6_22

We performed an investigation of how several data relationship discovery algorithms can be combined to improve performance. We investigated eight relationship discovery algorithms like Cosine similarity, Soundex similarity, Name similarity, Value ran... Read More about Ensemble-based relationship discovery in relational databases..

DRL-GAN: dual-stream representation learning GAN for low-resolution image classification in UAV applications. (2020)
Journal Article
XI, Y., JIA, W., ZHENG, J., FAN, X., XIE, Y., REN, J. and HE, X. 2021. DRL-GAN: dual-stream representation learning GAN for low-resolution image classification in UAV applications. IEEE Journal of selected topics in applied earth observations and remote sensing [online], 14, pages 1705-1716. Available from: https://doi.org/10.1109/JSTARS.2020.3043109

Identifying tiny objects from extremely low resolution (LR) UAV-based remote sensing images is generally considered as a very challenging task, because of very limited information in the object areas. In recent years, there have been very limited att... Read More about DRL-GAN: dual-stream representation learning GAN for low-resolution image classification in UAV applications..

EACOFT: an energy-aware correlation filter for visual tracking. (2020)
Journal Article
LIU, Q., REN, J., WANG, Y., WU, Y., SUN, H. and ZHAO, H. 2021. EACOFT: an energy-aware correlation filter for visual tracking. Pattern recognition [online], 112, article ID 107766. Available from: https://doi.org/10.1016/j.patcog.2020.107766

Correlation filter based trackers attribute to its calculation in the frequency domain can efficiently locate targets in a relatively fast speed. This characteristic however also limits its generalization in some specific scenarios. The reasons that... Read More about EACOFT: an energy-aware correlation filter for visual tracking..

Personalised meta-learning for human activity recognition with few-data. (2020)
Conference Proceeding
WIJEKOON, A. and WIRATUNGA, N. 2020. Personalised meta-learning for human activity recognition with few-data. In Bramer, M. and Ellis, R. (eds.) Artificial intelligence XXXVII: proceedings of 40th British Computer Society's Specialist Group on Artificial Intelligence (SGAI) Artificial intelligence international conference 2020 (AI-2020), 15-17 December 2020, [virtual conference]. Lecture notes in artificial intelligence, 12498. Cham: Springer [online], pages 79-93. Available from: https://doi.org/10.1007/978-3-030-63799-6_6

State-of-the-art methods of Human Activity Recognition(HAR) rely on a considerable amount of labelled data to train deep architectures. This becomes prohibitive when tasked with creating models that are sensitive to personal nuances in human movement... Read More about Personalised meta-learning for human activity recognition with few-data..

Computing degree apprenticeships: an opportunity to address gender imbalance in the IT sector? (2020)
Conference Proceeding
SMITH, S., TAYLOR-SMITH, E., FABIAN, K., BARR, M., BERG, T., CUTTING, D., PATERSON, J., YOUNG, T. and ZARB, M. 2020. Computing degree apprenticeships: an opportunity to address gender imbalance in the IT sector? In Proceedings of 2020 Institute of Electrical and Electronics Engineers (IEEE) Frontiers in education conference (FIE 2020), 21-24 October 2020, [virtual conference]. Piscataway: IEEE [online], article ID 9274144. Available from: https://doi.org/10.1109/FIE44824.2020.9274144

This paper explores the potential for new work-based apprenticeship degrees to encourage more women into computing degrees and the IT sector. In the UK, women are currently under-represented on computing courses. Meanwhile the IT industry requires mo... Read More about Computing degree apprenticeships: an opportunity to address gender imbalance in the IT sector?.

Professional communication tools in higher education: a case study in implementing slack in the curriculum. (2020)
Conference Proceeding
MENZIES, R. and ZARB, M. 2020. Professional communication tools in higher education: a case study in implementing slack in the curriculum. In Proceedings of 2020 Institute of Electrical and Electronics Engineers (IEEE) Frontiers in education conference (FIE 2020), 21-24 October 2020, [virtual conference]. Piscataway: IEEE [online], article ID 9273906. Available from: https://doi.org/10.1109/FIE44824.2020.9273906

This Innovative Practice Full Paper presents a study which considers the implications of embedding professional communication tools within the computing curriculum. Computing students are comfortable using various communication tools such as social m... Read More about Professional communication tools in higher education: a case study in implementing slack in the curriculum..

Analysing the learning by developing action model in HE computing. (2020)
Conference Proceeding
LINTILÄ, T. and ZARB, M. 2020. Analysing the learning by developing action model in HE computing. In Proceedings of 2020 Institute of Electrical and Electronics Engineers (IEEE) Frontiers in education conference (FIE 2020), 21-24 October 2020, [virtual conference]. Piscataway: IEEE [online], article ID 9274282. Available from: https://doi.org/10.1109/FIE44824.2020.9274282

This Research to Practice Working Process presents the first phase of the study, in which background information was sought from the literature and by interviews pedagogical experts from Laurea University of Applied Sciences (Laurea). The background... Read More about Analysing the learning by developing action model in HE computing..

Object recognition using enhanced particle swarm optimization. (2020)
Conference Proceeding
WILLIS, M., ZHANG, L., LIU, H., XIE, H. and MISTRY, L. 2020. Object recognition using enhanced particle swarm optimization. In Proceedings of 2020 International conference machine learning and cybernetics (ICMLC 2020), 4 December 2020, [virtual conference]. Piscataway: IEEE [online], pages 241-246. Available from: https://doi.org/10.1109/ICMLC51923.2020.9469584

The identification of the most discriminative features in an explainable AI decision-making process is a challenging problem. This research tackles such challenges by proposing Particle Swarm Optimization (PSO) variants embedded with novel mutation a... Read More about Object recognition using enhanced particle swarm optimization..

In-house deep environmental sentience for smart homecare solutions toward ageing society. (2020)
Conference Proceeding
EASOM, P., BOURIDANE, A., QIANG, F., DOWNS, C. and JIANG, R. 2020. In-house deep environmental sentience for smart homecare solutions toward ageing society. In Proceedings of 2020 International conference machine learning and cybernetics (ICMLC 2020), 4 December 2020, [virtual conference]. Piscataway: IEEE [online], pages 261-266. Available from: https://doi.org/10.1109/ICMLC51923.2020.9469531

With an increasing amount of elderly people needing home care around the clock, care workers are not able to keep up with the demand of providing maximum support to those who require it. As medical costs of home care increase the quality is care suff... Read More about In-house deep environmental sentience for smart homecare solutions toward ageing society..

On the class overlap problem in imbalanced data classification. (2020)
Journal Article
VUTTIPITTAYAMONGKOL, P., ELYAN, E. and PETROVSKI, A. 2021. On the class overlap problem in imbalanced data classification. Knowledge-based systems [online], 212, article number 106631. Available from: https://doi.org/10.1016/j.knosys.2020.106631

Class imbalance is an active research area in the machine learning community. However, existing and recent literature showed that class overlap had a higher negative impact on the performance of learning algorithms. This paper provides detailed criti... Read More about On the class overlap problem in imbalanced data classification..

Texture-sensitive superpixeling and adaptive thresholding for effective segmentation of sea ice floes in high-resolution optical images. (2020)
Journal Article
CHAI, Y., REN, J., HWANG, B., WANG, J., FAN, D., YAN, Y. and ZHU, S. 2021. Texture-sensitive superpixeling and adaptive thresholding for effective segmentation of sea ice floes in high-resolution optical images. IEEE journal of selected topics in applied earth observations and remote sensing [online], 14, pages 577-586. Available from: https://doi.org/10.1109/jstars.2020.3040614

Efficient and accurate segmentation of sea ice floes from high-resolution optical (HRO) remote sensing images is crucial for understanding of sea ice evolutions and climate changes, especially in coping with the large data volume. Existing methods su... Read More about Texture-sensitive superpixeling and adaptive thresholding for effective segmentation of sea ice floes in high-resolution optical images..

Multiscale 2-D singular spectrum analysis and principal component analysis for spatial–spectral noise-robust feature extraction and classification of hyperspectral images. (2020)
Journal Article
MA, P., REN, J., ZHAO, H., SUN, G., MURRAY, P. and ZHENG, J. 2021. Multiscale 2-D singular spectrum analysis and principal component analysis for spatial–spectral noise-robust feature extraction and classification of hyperspectral images. IEEE journal of selected topics in applied earth observations and remote sensing [online], 14, pages 1233-1245. Available from: https://doi.org/10.1109/JSTARS.2020.3040699

In hyperspectral images (HSI), most feature extraction and data classification methods rely on corrected dataset, in which the noisy and water absorption bands are removed. This can result in not only extra working burden but also information loss fr... Read More about Multiscale 2-D singular spectrum analysis and principal component analysis for spatial–spectral noise-robust feature extraction and classification of hyperspectral images..

Applying acceptance requirements to requirements modeling tools via gamification: a case study on privacy and security. (2020)
Conference Proceeding
PIRAS, L., CALABRESE, F. and GIORGINI, P. 2020. Applying acceptance requirements to requirements modeling tools via gamification: a case study on privacy and security. In Grabis, J. and Bork, D. (eds.) The practice of enterprise modeling: proceedings of 13th International Federation for Information Processing (IFIP) Practice of enterprise modelling working conference 2020 (Poem 2020), 25-27 November 2020, Riga, Latvia. Lecture notes in business information processing, 400. Cham: Springer [online], pages 366-376. Available from: https://doi.org/10.1007/978-3-030-63479-7_25

Requirements elicitation, analysis and modeling are critical activities for software success. However, software systems are increasingly complex, harder to develop due to an ever-growing number of requirements from numerous and heterogeneous stakehol... Read More about Applying acceptance requirements to requirements modeling tools via gamification: a case study on privacy and security..

A homogeneous-heterogeneous ensemble of classifiers. (2020)
Conference Proceeding
LUONG, A.V., VU, T.H., NGUYEN, P.M., VAN PHAM, N., MCCALL, J., LIEW, A.W.-C. and NGUYEN, T.T. 2020. A homogeneous-heterogeneous ensemble of classifiers. In Yang, H., Pasupa, K., Leung, A.C.-S., Kwok, J.T., Chan, J.H. and King, I. (eds.) Neural information processing: proceedings of 27th International conference on neural information processing 2020 (ICONIP 2020), part 5. Communications in computer and information science, 1333. Cham: Springer [online], pages, 251-259. Available from: https://doi.org/10.1007/978-3-030-63823-8_30

In this study, we introduce an ensemble system by combining homogeneous ensemble and heterogeneous ensemble into a single framework. Based on the observation that the projected data is significantly different from the original data as well as each ot... Read More about A homogeneous-heterogeneous ensemble of classifiers..

Toward an ensemble of object detectors. (2020)
Conference Proceeding
DANG, T., NGUYEN, T.T. and MCCALL, J. 2020. Toward an ensemble of object detectors. In Yang, H., Pasupa, K., Leung, A.C.-S., Kwok, J.T., Chan, J.H. and King, I. (eds.) Neural information processing: proceedings of 27th International conference on neural information processing 2020 (ICONIP 2020), part 5. Communications in computer and information science, 1333. Cham: Springer [online], pages, 458-467. Available from: https://doi.org/10.1007/978-3-030-63823-8_53

The field of object detection has witnessed great strides in recent years. With the wave of deep neural networks (DNN), many breakthroughs have achieved for the problems of object detection which previously were thought to be difficult. However, ther... Read More about Toward an ensemble of object detectors..