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Learning from small and imbalanced dataset of images using generative adversarial neural networks. (2019)
Thesis
ALI-GOMBE, A. 2019. Learning from small and imbalanced dataset of images using generative adversarial neural networks. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

The performance of deep learning models is unmatched by any other approach in supervised computer vision tasks such as image classification. However, training these models requires a lot of labeled data, which are not always available. Labelling a ma... Read More about Learning from small and imbalanced dataset of images using generative adversarial neural networks..

Food survey using exploratory data analysis. (2019)
Conference Proceeding
RAMYASRI, R., ISHASANJIDA, S., PARASA, D. and BANO, S. 2019. Food survey using exploratory data analysis. In Proceedings of the 2nd International conference on intelligent communication and computational techniques (ICCT 2019), 28-29 September 2019, Jaipur, India. Piscataway: IEEE [online], pages 258-264. Available from: https://doi.org/10.1109/ICCT46177.2019.8969016

A person's eating habits are the most important aspect of maintaining one's physical wellbeing, which in turn is key to enduring the stresses and emotional hurdles that are so commonplace in our modern lifestyles. Our research shows that, over the pa... Read More about Food survey using exploratory data analysis..

Social media survey using decision tree and naive Bayes classification. (2019)
Conference Proceeding
ROSHINI, T., SIREESHA, P.V., PARASA, D. and BANO, S. 2019. Social media survey using decision tree and naive Bayes classification. In Proceedings of the 2nd International conference on intelligent communication and computational techniques (ICCT 2019), 28-29 September 2019, Jaipur, India. Piscataway: IEEE [online], pages 265-270. Available from: https://doi.org/10.1109/ICCT46177.2019.8969058

Social media - a website or an application that is used to create and share content among a social network - is one of the most important aspects of our day-to-day life. Recent studies claim that an average person spends roughly 142 minutes per day o... Read More about Social media survey using decision tree and naive Bayes classification..

Classification of binary fracture using CNN. (2019)
Conference Proceeding
CHITTAJALLU, S.M., MANDALANENI, N.L.D., PARASA, D. and BANO, S. 2019. Classification of binary fracture using CNN. In Proceedings of the 1st Global conference for advancement in technology (GCAT 2019), 18-20 October 2019, Bangalore, India. Piscataway: IEEE [online]. Available from: https://doi.org/10.1109/GCAT47503.2019.8978468

One of the major problems faced by any living organism since infancy are musculoskeletal injuries. To keep it quite simple musculoskeletal injuries are a range of disorders involving muscles, bones, tendons, blood vessels, nerves and other soft tissu... Read More about Classification of binary fracture using CNN..

Food places classification in egocentric images using Siamese neural networks. (2019)
Conference Proceeding
SARKER, M.M.K., BANU, S.F., RASHWAN, H.A., ABDEL-NASSER, M., SINGH, V.K., CHAMBON, S., RADEVA, P. and PUIG, D. 2019. Food places classification in egocentric images using Siamese neural networks. In Sabater-Mir, J., Torra, V., Aguiló, I. and González-Hidalgo, M. (eds.) Artificial intelligence research and development: proceedings of the 22nd International conference of the Catalan Association for Artificial Intelligence (CCIA 2019), 23-25 October 2019, Colònia de Sant Jordi, Spain. Frontiers in artificial intelligence and applications, 319. Amsterdam: IOS Press [online], pages 145-151. Available from: https://doi.org/10.3233/FAIA190117

Wearable cameras have become more popular in recent years for capturing unscripted moments in the first-person, which help in analysis of the user's lifestyle. In this work, we aim to identify the daily food patterns of a person through recognition o... Read More about Food places classification in egocentric images using Siamese neural networks..

Generation and optimisation of real-world static and dynamic location-allocation problems with application to the telecommunications industry. (2019)
Thesis
ANKRAH, R.B. 2019. Generation and optimisation of real-world static and dynamic location-allocation problems with application to the telecommunications industry. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

The location-allocation (LA) problem concerns the location of facilities and the allocation of demand, to minimise or maximise a particular function such as cost, profit or a measure of distance. Many formulations of LA problems have been presented i... Read More about Generation and optimisation of real-world static and dynamic location-allocation problems with application to the telecommunications industry..

Deep heterogeneous ensemble. (2019)
Journal Article
NGUYEN, T.T., DANG, M.T., PHAM, T.D., DAO, L.P., LUONG, A.V., MCCALL, J. and LIEW, A.W.C. 2019. Deep heterogeneous ensemble. Australian journal of intelligent information processing systems [online], 16(1): special issue on neural information processing: proceedings of the 26th International conference on neural information processing (ICONIP 2019), 12-15 December 2019, Sydney, Australia, pages 1-9. Available from: http://ajiips.com.au/papers/V16.1/v16n1_5-13.pdf

In recent years, deep neural networks (DNNs) have emerged as a powerful technique in many areas of machine learning. Although DNNs have achieved great breakthrough in processing images, video, audio and text, it also has some limitations... Read More about Deep heterogeneous ensemble..

Integrating selection-based aspect sentiment and preference knowledge for social recommender systems. (2019)
Journal Article
CHEN, Y.Y., WIRATUNGA, N. and LOTHIAN, R. 2020. Integrating selection-based aspect sentiment and preference knowledge for social recommender systems. Online information review [online], 44(2), pages 399-416. Available from: https://doi.org/10.1108/OIR-02-2017-0066

Purpose: Recommender system approaches such as collaborative and content-based filtering rely on user ratings and product descriptions to recommend products. More recently, recommender system research has focussed on exploiting knowledge from user-ge... Read More about Integrating selection-based aspect sentiment and preference knowledge for social recommender systems..

Evolving an optimal decision template for combining classifiers. (2019)
Conference Proceeding
NGUYEN, T.T., LUONG, A.V., DANG, M.T., DAO, L.P., NGUYEN, T.T.T., LIEW, A.W.-C. and MCCALL, J. 2019. Evolving an optimal decision template for combining classifiers. In Gedeon, T., Wong, K.W. and Lee, M. (eds.) Neural information processing: proceedings of the 26th International conference on neural information processing (ICONIP 2019), 12-15 December 2019, Sydney, Australia. Part I. Lecture notes in computer science, 11953. Cham: Springer [online], pages 608-620. Available from: https://doi.org/10.1007/978-3-030-36708-4_50

In this paper, we aim to develop an effective combining algorithm for ensemble learning systems. The Decision Template method, one of the most popular combining algorithms for ensemble systems, does not perform well when working on certain datasets l... Read More about Evolving an optimal decision template for combining classifiers..

A comparison of feature extractors for panorama stitching in an autonomous car architecture. (2019)
Conference Proceeding
CORTÉS-GALLARDO, E., MORENO-GARCIA, C.F., ZHU, A., CHÍPULI-SILVA, D., GONZÁLEZ-GONZÁLEZ, J.A., MORALES-ORTIZ, D., FERNÁNDEZ, S., URRIZA, B., VALVERDE-LÓPEZ, J., MARÍN, A., PÉREZ, H., IZQUIERDO-REYES, J. and BUSTAMANTE-BELLO, R. 2019. A comparison of feature extractors for panorama stitching in an autonomous care architecture. In Proceedings of 2019 International conference on mechatronics, electronics and automotive engineering (ICMEAE 2019), 26-29 November 2019, Cuernavaca, Mexico. Piscataway: IEEE [online], page 50-55. Available from: https://doi.org/10.1109/ICMEAE.2019.00017

Panorama stitching consists on frames being put together to create a 360o view. This technique is proposed for its implementation in autonomous vehicles instead of the use of an external 360o camera, mostly due to its reduced cost and improved aerody... Read More about A comparison of feature extractors for panorama stitching in an autonomous car architecture..

Developing a catalogue of explainability methods to support expert and non-expert users. (2019)
Conference Proceeding
MARTIN, K., LIRET, A., WIRATUNGA, N., OWUSU, G. and KERN, M. 2019. Developing a catalogue of explainability methods to support expert and non-expert users. In Bramer, M. and Petridis, M. (eds.) Artificial intelligence XXXVI: proceedings of the 39th British Computer Society's Specialist Group on Artificial Intelligence (SGAI) international Artificial intelligence conference 2019 (AI 2019), 17-19 December 2019, Cambridge, UK. Lecture notes in computer science, 11927. Cham: Springer [online], pages 309-324. Available from: https://doi.org/10.1007/978-3-030-34885-4_24

Organisations face growing legal requirements and ethical responsibilities to ensure that decisions made by their intelligent systems are explainable. However, provisioning of an explanation is often application dependent, causing an extended design... Read More about Developing a catalogue of explainability methods to support expert and non-expert users..

Multi-objective evolutionary design of antibiotic treatments. (2019)
Journal Article
OCHOA, G., CHRISTIE, L.A., BROWNLEE, A.E. and HOYLE, A. 2020. Multi-objective evolutionary design of antibiotic treatments. Artificial intelligence in medicine [online], 102, article number 101759. Available from: https://doi.org/10.1016/j.artmed.2019.101759

Antibiotic resistance is one of the major challenges we face in modern times. Antibiotic use, especially their overuse, is the single most important driver of antibiotic resistance. Efforts have been made to reduce unnecessary drug prescriptions, but... Read More about Multi-objective evolutionary design of antibiotic treatments..

Towards a conversational agent for threat detection in the internet of things. (2019)
Conference Proceeding
MCDERMOTT, C.D., JEANNELLE, B. and ISAACS, J.P. 2019. Towards a conversational agent for threat detection in the internet of things. In Proceedings of the 2019 International Cyber science on cyber situational awareness, data analytics and assessment (Cyber SA): pioneering research and innovation in cyber situational awareness, 3-4 June 2019, Oxford, UK. Piscataway: IEEE [online], chapter 6. Available from: https://doi.org/10.1109/CyberSA.2019.8899580

A conversational agent to detect anomalous traffic in consumer IoT networks is presented. The agent accepts two inputs in the form of user speech received by Amazon Alexa enabled devices, and classified IDS logs stored in a DynamoDB Table. Aural anal... Read More about Towards a conversational agent for threat detection in the internet of things..

The effects of measurement error and testing frequency on the fitness-fatigue model applied to resistance training: a simulation approach. (2019)
Journal Article
STEPHENS HEMINGWAY, B.H., BURGESS, K.E., ELYAN, E. and SWINTON, P.A. 2020. The effects of measurement error and testing frequency on the fitness-fatigue model applied to resistance training: a simulation approach. International journal of sports science and coaching [online], 15(1), pages 60-71. Available from: https://doi.org/10.1177/1747954119887721

This study investigated the effects of measurement error and testing frequency on prediction accuracy of the standard fitness-fatigue model. A simulation-based approach was used to systematically assess measurement error and frequency inputs commonly... Read More about The effects of measurement error and testing frequency on the fitness-fatigue model applied to resistance training: a simulation approach..

Ensemble selection based on classifier prediction confidence. (2019)
Journal Article
NGUYEN, T.T., LUONG, A.V., DANG, M.T., LIEW, A.W.-C. and MCCALL, J. 2020. Ensemble selection based on classifier prediction confidence. Pattern recognition [online], 100, article ID 107104. Available from: https://doi.org/10.1016/j.patcog.2019.107104

Ensemble selection is one of the most studied topics in ensemble learning because a selected subset of base classifiers may perform better than the whole ensemble system. In recent years, a great many ensemble selection methods have been introduced.... Read More about Ensemble selection based on classifier prediction confidence..

Reducing computational cost in IoT cyber security: case study of artificial immune system algorithm. (2019)
Conference Proceeding
ZAKARIYYA, I., AL-KADRI, M.O., KALUTARGE, H. and PETROVSKI, A. 2019. Reducing computational cost in IoT cyber security: case study of artificial immune system algorithm. In Obaidat, M. and Samarati, P. (eds.) Proceedings of the 16th International security and cryptography conference (SECRYPT 2019), co-located with the 16th International joint conference on e-business and telecommunications (ICETE 2019), 26-28 July 2019, Prague, Czech Republic. Setúbal, Portugal: SciTePress [online], 2, pages 523-528. Available from: https://doi.org/10.5220/0008119205230528.

Using Machine Learning (ML) for Internet of Things (IoT) security monitoring is a challenge. This is due to their resource constraint nature that limits the deployment of resource-hungry monitoring algorithms. Therefore, the aim of this paper is to i... Read More about Reducing computational cost in IoT cyber security: case study of artificial immune system algorithm..

Design thinking and acceptance requirements for designing gamified software. (2019)
Conference Proceeding
PIRAS, L., DELLAGIACOMA, D., PERINI, A., SUSI, A., GIORGINI, P. and MYLOPOULOS, J. 2019. Design thinking and acceptance requirements for designing gamified software. In Kolp, M., Vanderdonckt, J., Snoeck, M. and Wautelet, Y. (eds.) Proceedings of 13th Institute of Electrical and Electronics Engineers (IEEE) Research challenges in information science international conference 2019 (RICS 2019): towards a design science for information systems, 29-31 May 2019, Brussels, Belgium. Piscataway: IEEE [online], pages 81-92. Available from: https://doi.org/10/1109/RCIS.2019.8876973

Gamification is increasingly applied to engage people in performing tool-supported collaborative tasks. From previous experiences we learned that available gamification guidelines are not sufficient, and more importantly that motivational and accepta... Read More about Design thinking and acceptance requirements for designing gamified software..

When is quality assurance a constructive force in engineering education? (2019)
Conference Proceeding
PEARS, A., DANIELS, M., NYLEN, A., and MCDERMOTT, R. 2020. When is quality assurance a constructive force in engineering education? In Proceedings of the 49th Institute of Electrical and Electronics Engineers (IEEE) Frontiers in education conference 2019 (FIE 2019): bridging education to the future, 16-19 October 2019, Cincinnati, USA. Piscataway: IEEE [online], article ID 9028377. Available from: https://doi.org/10.1109/FIE43999.2019.9028377

Quality assurance processes in education have been a key area of engineering education development for several decades. ABET, ENQA - The European Association for Quality Assurance in Higher Education, as well as other agencies in Europe and the Asia... Read More about When is quality assurance a constructive force in engineering education?.

Combining t-distributed stochastic neighbor embedding with convolutional neural networks for hyperspectral image classification. (2019)
Journal Article
GAO, L., GU, D., ZHUANG, L., REN, J., YANG, D. and ZHANG, B. 2020. Combining t-distributed stochastic neighbor embedding with convolutional neural networks for hyperspectral image classification. IEEE geoscience and remote sensing letters [online], 17(8), pages 1368-1372. Available from: https://doi.org/10.1109/LGRS.2019.2945122

Hyperspectral images (HSIs), featured by high spectral resolution over a wide range of electromagnetic spectra, have been widely used to characterize materials with subtle differences in the spectral domain. However, a large number of bands and an in... Read More about Combining t-distributed stochastic neighbor embedding with convolutional neural networks for hyperspectral image classification..

Data stream mining: methods and challenges for handling concept drift. (2019)
Journal Article
WARES, S., ISAACS, J. and ELYAN, E. 2019. Data stream mining: methods and challenges for handling concept drift. SN applied sciences [online], 1(11), article ID 1412. Available from: https://doi.org/10.1007/s42452-019-1433-0

Mining and analysing streaming data is crucial for many applications, and this area of research has gained extensive attention over the past decade. However, there are several inherent problems that continue to challenge the hardware and the state-of... Read More about Data stream mining: methods and challenges for handling concept drift..