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All Outputs (35)

Bespoke anywhere (2021)
Conference Proceeding
Gaster, B., & Challinor, R. (2021). Bespoke anywhere.

This paper reports on a project aimed to break away from the portability concerns of native DSP code between different platforms, thus freeing the instrument designer from the burden of porting new Digital Musical Instruments (DMIs) to different arch... Read More about Bespoke anywhere.

Automatic for the people: Crowd-driven generative scores using Manhattan and machine vision (2021)
Conference Proceeding
Nash, C. (2021). Automatic for the people: Crowd-driven generative scores using Manhattan and machine vision.

This paper details a workshop and optional public installation based on the development of situational scores that combine music notation, AI, and code to create dynamic interactive art driven by the realtime movements of objects and people in a live... Read More about Automatic for the people: Crowd-driven generative scores using Manhattan and machine vision.

Analysing the effect of food supply chain traceability on product waste (2021)
Conference Proceeding
Glew, M. R., Perez Hernandez, M., & McFarlane, D. (2021). Analysing the effect of food supply chain traceability on product waste. In M. Fakhimi, T. Boness, & D. Robertson (Eds.), Proceedings of the Operational Research Society Simulation Workshop 2021 (SW21) (145-154)

This paper presents initial results from an agent-based simulation study into the impact of supply chain traceability information sharing on food waste reduction in the fresh food supply chain. Based on data collected during a 2019 study of a multi-t... Read More about Analysing the effect of food supply chain traceability on product waste.

The role of text analytics in healthcare: A review of recent developments and applications (2021)
Conference Proceeding
Elbattah, M., Arnaud, É., Gignon, M., & Dequen, G. (2021). The role of text analytics in healthcare: A review of recent developments and applications. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (825-832). https://doi.org/10.5220/0010414508250832

The implementation of Data Analytics has achieved a significant momentum across a very wide range of domains. Part of that progress is directly linked to the implementation of Text Analytics solutions. Organisations increasingly seek to harness the p... Read More about The role of text analytics in healthcare: A review of recent developments and applications.

Modeling diseases with Stream X Machine (2021)
Conference Proceeding
Jayatilake, S., Ogunshile, E., Aydin, M., & Phung, K. (2021). Modeling diseases with Stream X Machine. In 2021 9th International Conference in Software Engineering Research and Innovation (CONISOFT) (61-68). https://doi.org/10.1109/CONISOFT52520.2021.00020

At present the world is moving towards alternative medicine and behavioural alteration for treating, managing, and preventing chronical diseases. With the individuality of the human beings has added more complexity in a domain where very high accurac... Read More about Modeling diseases with Stream X Machine.

A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning (2021)
Conference Proceeding
Phung, K., Ogunshile, E., & Aydin, M. (2021). A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning. In 2021 9th International Conference in Software Engineering Research and Innovation (CONISOFT) (168-179). https://doi.org/10.1109/CONISOFT52520.2021.00032

Software fault prediction makes software quality assurance process more efficient and economic. Most of the works related to software fault prediction have mainly focused on classifying software modules as faulty or not, which does not produce suffic... Read More about A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning.

The application of eye-tracking technology in architecture engineering and construction industry: A systematic review (2021)
Conference Proceeding
Mahamadu, A., Prabhakaran, A., Clark, K., Dziekonski, K., Okeke, U., Zhang, W., …Aigbavboa, C. O. (2021). The application of eye-tracking technology in architecture engineering and construction industry: A systematic review. In N. Dawood, F. Pour Rahimian, & M. Sheikhkhoshkar (Eds.), Proceedings of the 21st International Conference on Construction Applications of Virtual Reality (56-64)

Despite the scholarly attention on eye-tracking technology in the AEC industry, no studies thus far have attempted to aggregate the findings or knowledge. To bridge this gap and to better understand the state-of-the-art of eye-tracking technology’s a... Read More about The application of eye-tracking technology in architecture engineering and construction industry: A systematic review.

API security in large enterprises: Leveraging machine learning for anomaly detection (2021)
Conference Proceeding
Baye, G., Hussain, F., Oracevic, A., Hussain, R., & Ahsan Kazmi, S. (2021). API security in large enterprises: Leveraging machine learning for anomaly detection. In 2021 International Symposium on Networks, Computers and Communications (ISNCC) (1-6). https://doi.org/10.1109/ISNCC52172.2021.9615638

Large enterprises offer thousands of micro-services applications to support their daily business activities by using Application Programming Interfaces (APIs). These applications generate huge amounts of traffic via millions of API calls every day, w... Read More about API security in large enterprises: Leveraging machine learning for anomaly detection.

Modern stylometry: A review & experimentation with machine learning (2021)
Conference Proceeding
Muldoon, C., Ikram, A., & Khan Mirza, Q. A. (2021). Modern stylometry: A review & experimentation with machine learning. In 2021 8th International Conference on Future Internet of Things and Cloud (FiCloud), 2021 (293-298). https://doi.org/10.1109/FiCloud49777.2021.00049

The problem of authorship attribution has applications from literary studies (such as the great Shakespeare/Marlowe debates) to counter-intelligence. The field of stylometry aims to offer quantitative results for authorship attribution. In this paper... Read More about Modern stylometry: A review & experimentation with machine learning.

Statistical disclosure controls for machine learning models (2021)
Conference Proceeding
Krueger, S., Mansouri-Benssassi, E., Ritchie, F., & Smith, J. (2021). Statistical disclosure controls for machine learning models

Artificial Intelligence (AI) models are trained on large datasets. Where the training data is sensitive, the data holders need to consider risks posed by access to the training data and risks posed by the models that are released. The first problem c... Read More about Statistical disclosure controls for machine learning models.

Establishing the informational requirements for modelling open domain dialogue and prototyping a retrieval open domain dialogue system (2021)
Conference Proceeding
Meier, T., & Pimenidis, E. (2021). Establishing the informational requirements for modelling open domain dialogue and prototyping a retrieval open domain dialogue system. In N. Nguyen, L. Iliadis, I. Maglogiannis, & B. Trawiński (Eds.), Computational Collective Intelligence (655-667). https://doi.org/10.1007/978-3-030-88081-1_49

Open domain dialogue systems aim to coherently respond to users over long conversations through multiple conversational turns. Modelling open domain dialogue is challenging as both the syntactic and semantic features of language play a role in respon... Read More about Establishing the informational requirements for modelling open domain dialogue and prototyping a retrieval open domain dialogue system.

Social influence prediction with train and test time augmentation for graph neural networks (2021)
Conference Proceeding
Bo, H., McConville, R., Hong, J., & Liu, W. (2021). Social influence prediction with train and test time augmentation for graph neural networks. In Proceedings of the International Joint Conference on Neural Networks 2021 (IJCNN 2021)https://doi.org/10.1109/IJCNN52387.2021.9533437

Data augmentation has been widely used in machine learning for natural language processing and computer vision tasks to improve model performance. However, little research has studied data augmentation on graph neural networks, particularly using aug... Read More about Social influence prediction with train and test time augmentation for graph neural networks.

Reinforcement learning-based adaptive operator selection (2021)
Conference Proceeding
Durgut, R., & Aydin, M. E. (2021). Reinforcement learning-based adaptive operator selection. In B. Dorronsoro, L. Amodeo, M. Pavone, & P. Ruiz (Eds.), . https://doi.org/10.1007/978-3-030-85672-4_3

Metaheuristic and swarm intelligence approaches require devising optimisation algorithms with operators to let produce neighbouring solutions to conduct a move. The efficiency of algorithms using single operator remains recessive in comparison with t... Read More about Reinforcement learning-based adaptive operator selection.

A strategic search algorithm in multi-agent and multiple target environment (2021)
Conference Proceeding
Afzalov, A., Lotfi, A., & Aydin, M. E. (2021). A strategic search algorithm in multi-agent and multiple target environment. In E. Chew, A. P. Abdul Majeed, P. Liu, J. Platts, H. Myung, J. Kim, & J. Kim (Eds.), RiTA 2020 (195-204). https://doi.org/10.1007/978-981-16-4803-8_21

The aim of this study is to investigate how to solve the path-planning problem of multiple competing players towards moving targets within a dynamically changing environment. A novel approach is needed to exceed the classical solutions for single or... Read More about A strategic search algorithm in multi-agent and multiple target environment.

NLP-based prediction of medical specialties at hospital admission using triage notes (2021)
Conference Proceeding
Arnaud, E., Elbattah, M., Gignon, M., & Dequen, G. (2021). NLP-based prediction of medical specialties at hospital admission using triage notes. In 2021 IEEE 9th International Conference on Healthcare Informatics (ICHI) (548-553). https://doi.org/10.1109/ichi52183.2021.00103

Data Analytics is rapidly expanding within the healthcare domain to help develop strategies for improving the quality of care and curbing costs as well. Natural Language Processing (NLP) solutions have received particular attention whereas a large pa... Read More about NLP-based prediction of medical specialties at hospital admission using triage notes.

Comparison of agent deployment strategies for collaborative prognosis (2021)
Conference Proceeding
Dhada, M., Hernandez, M. P., Salvador Palau, A., & Parlikad, A. (2021). Comparison of agent deployment strategies for collaborative prognosis. In 2021 IEEE International Conference on Prognostics and Health Management (ICPHM)https://doi.org/10.1109/ICPHM51084.2021.9486628

Collaborative prognosis is a technique that enables the industrial assets to learn from similar other assets in a fleet, and improve their data-driven prognosis models. When collaborative prognosis is implemented in a computationally distributed fram... Read More about Comparison of agent deployment strategies for collaborative prognosis.

A comparative analysis for binary search operators used in artificial bee colony (2021)
Conference Proceeding
Atli, I., Durgut, R., & Aydin, M. E. (2021). A comparative analysis for binary search operators used in artificial bee colony. In 2021 29th Signal Processing and Communications Applications Conference (SIU). https://doi.org/10.1109/SIU53274.2021.9477907

Metaheuristic optimization algorithms are developed to find the best or near-best solutions within a reasonable time frame utilizing various neighbourhood functions (i.e., operators). Variety of studies have been proposed for structural modifications... Read More about A comparative analysis for binary search operators used in artificial bee colony.

Feature vulnerability and robustness assessment against adversarial machine learning attacks (2021)
Conference Proceeding
Mccarthy, A., Andriotis, P., Ghadafi, E., & Legg, P. (2021). Feature vulnerability and robustness assessment against adversarial machine learning attacks. In 2021 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA). https://doi.org/10.1109/CyberSA52016.2021.9478199

Whilst machine learning has been widely adopted for various domains, it is important to consider how such techniques may be susceptible to malicious users through adversarial attacks. Given a trained classifier, a malicious attack may attempt to craf... Read More about Feature vulnerability and robustness assessment against adversarial machine learning attacks.

"Hacking an IoT Home": New opportunities for cyber security education combining remote learning with cyber-physical systems (2021)
Conference Proceeding
Legg, P., Higgs, T., Spruhan, P., White, J., & Johnson, I. (2021). "Hacking an IoT Home": New opportunities for cyber security education combining remote learning with cyber-physical systems. In 2021 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA). https://doi.org/10.1109/CyberSA52016.2021.9478251

In March 2020, the COVID-19 pandemic led to a dramatic shift in educational practice, whereby home-schooling and remote working became the norm. Many typical schools outreach projects to encourage uptake of learning cyber security skills therefore we... Read More about "Hacking an IoT Home": New opportunities for cyber security education combining remote learning with cyber-physical systems.