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All Outputs (38)

Mining the Irish hip fracture database: Learning factors contributing to care outcomes (2020)
Journal Article
Elbattah, M., & Molloy, O. (2020). Mining the Irish hip fracture database: Learning factors contributing to care outcomes. International Journal of Data Science, 5(4), 290. https://doi.org/10.1504/ijds.2020.115875

Data analytics has opened the door for improving many aspects pertaining to the delivery of healthcare. This study avails of unsupervised machine learning to extract knowledge from the Irish hip fracture database (IHFD). The dataset under considerati... Read More about Mining the Irish hip fracture database: Learning factors contributing to care outcomes.

Elicitation of the factors affecting electricity distribution efficiency using the fuzzy AHP method (2020)
Journal Article
Yiğit, V., Demir, N. N., Alidrisi, H., & Aydin, M. E. (2020). Elicitation of the factors affecting electricity distribution efficiency using the fuzzy AHP method. Mathematics, 9(1), 1-25. https://doi.org/10.3390/math9010082

Efficient and uninterrupted energy supply plays a crucial role in the quality of modern daily life, while it is obvious that the efficiency and performance of energy supply companies has a significant impact on energy supply itself and on determining... Read More about Elicitation of the factors affecting electricity distribution efficiency using the fuzzy AHP method.

In silico optimization of cancer therapies with multiple types of nanoparticles applied at different times (2020)
Journal Article
Tsompanas, M. A., Bull, L., Adamatzky, A., & Balaz, I. (2020). In silico optimization of cancer therapies with multiple types of nanoparticles applied at different times. Computer Methods and Programs in Biomedicine, 200, Article 105886. https://doi.org/10.1016/j.cmpb.2020.105886

© 2020 The Author(s) Background and Objective: Cancer tumors constitute a complicated environment for conventional anti-cancer treatments to confront, so solutions with higher complexity and, thus, robustness to diverse conditions are required. Alter... Read More about In silico optimization of cancer therapies with multiple types of nanoparticles applied at different times.

The natural connectivity of autonomous systems (2020)
Journal Article
Battle, S. (2020). The natural connectivity of autonomous systems. Rivista Italiana di Filosofia del Linguaggio, 14(2), 1-16. https://doi.org/10.4396/AISB201901

The principle of biological autonomy, introduced by Francisco J. Varela, addresses the dilemma of Cartesian mind-body dualism by re-casting mind and body, or subject and object, observer and observed, not as irreconcilable categories, but as compleme... Read More about The natural connectivity of autonomous systems.

Adaptive binary artificial bee colony algorithm (2020)
Journal Article
Durgut, R., & Aydin, M. E. (2021). Adaptive binary artificial bee colony algorithm. Applied Soft Computing, 101, Article 107054. https://doi.org/10.1016/j.asoc.2020.107054

Metaheuristics and swarm intelligence algorithms are bio-inspired algorithms, which have long standing track record of success in problem solving. Due to the nature and the complexity of the problems, problem solving approaches may not achieve the sa... Read More about Adaptive binary artificial bee colony algorithm.

Performance of deep learning vs machine learning in plant leaf disease detection (2020)
Journal Article
Sujatha, R., Chatterjee, J. M., Jhanjhi, N. Z., & Brohi, S. (2020). Performance of deep learning vs machine learning in plant leaf disease detection. Microprocessors and Microsystems, 80, 103615. https://doi.org/10.1016/j.micpro.2020.103615

Plants are recognized as essential as they are the primary source of humanity's energy production since they are having nutritious, medicinal, etc. values. At any time between crop farming, plant diseases can affect the leaf, resulting in enormous cr... Read More about Performance of deep learning vs machine learning in plant leaf disease detection.

Investigating anti-evasion malware triggers using automated sandbox reconfiguration techniques (2020)
Journal Article
Mills, A., & Legg, P. (2021). Investigating anti-evasion malware triggers using automated sandbox reconfiguration techniques. Journal of Cybersecurity and Privacy, 1(1), 19-39. https://doi.org/10.3390/jcp1010003

Malware analysis is fundamental for defending against prevalent cyber security threats and requires a means to deploy and study behavioural software traits as more sophisticated malware is developed. Traditionally, virtual machines are used to provid... Read More about Investigating anti-evasion malware triggers using automated sandbox reconfiguration techniques.

Deep learning vs. traditional solutions for group trajectory outliers (2020)
Journal Article
Belhadi, A., Djenouri, Y., Djenouri, D., Michalak, T., & Chun-Wei Lin, J. (2022). Deep learning vs. traditional solutions for group trajectory outliers. IEEE Transactions on Cybernetics, 52(6), 4508-4519. https://doi.org/10.1109/TCYB.2020.3029338

This article introduces a new model to identify a group of trajectory outliers from a large trajectory database and proposes several algorithms. These can be split into three categories: 1) algorithms based on data mining and knowledge discovery, whi... Read More about Deep learning vs. traditional solutions for group trajectory outliers.

Harnessing adaptive novelty for automated generation of cancer treatments (2020)
Journal Article
Balaz, I., Petrić, T., Kovacevic, M., Tsompanas, M. A., & Stillman, N. (2021). Harnessing adaptive novelty for automated generation of cancer treatments. BioSystems, 199, Article 104290. https://doi.org/10.1016/j.biosystems.2020.104290

© 2020 The Authors Nanoparticles have the potential to modulate both the pharmacokinetic and pharmacodynamic profiles of drugs, thereby enhancing their therapeutic effect. The versatility of nanoparticles allows for a wide range of customization poss... Read More about Harnessing adaptive novelty for automated generation of cancer treatments.

When the decomposition meets the constraint satisfaction problem (2020)
Journal Article
Djenouri, Y., Djenouri, D., Habbas, Z., Lin, J. C., Michalak, T. P., & Cano, A. (2020). When the decomposition meets the constraint satisfaction problem. IEEE Access, 8, 207034-207043. https://doi.org/10.1109/access.2020.3038228

This paper explores the joint use of decomposition methods and parallel computing for solving constraint satisfaction problems and introduces a framework called Parallel Decomposition for Constraint Satisfaction Problems (PD-CSP). The main idea is th... Read More about When the decomposition meets the constraint satisfaction problem.

Towards the identification of antibiotic-resistant bacteria causing urinary tract infections using volatile organic compounds analysis—a pilot study (2020)
Journal Article
Hewett, K., Drabinska, N., White, P., Avison, M., Persad, R., Ratcliffe, N., & de Lacy Costello, B. (2020). Towards the identification of antibiotic-resistant bacteria causing urinary tract infections using volatile organic compounds analysis—a pilot study. Antibiotics, 9(11), 797. https://doi.org/10.3390/antibiotics9110797

Antibiotic resistance is an unprecedented threat to modern medicine. The analysis of volatile organic compounds (VOCs) from bacteria potentially offers a rapid way to determine antibiotic susceptibility in bacteria. This study aimed to find the optim... Read More about Towards the identification of antibiotic-resistant bacteria causing urinary tract infections using volatile organic compounds analysis—a pilot study.

Assessing a decision support tool for SOC analysts (2020)
Journal Article
Happa, J., Helmhout, M., Philips, R., Thomas Bashford-Rogers, N. L., Goldsmith, M., Creese, S., …Goldsmith, M. (in press). Assessing a decision support tool for SOC analysts. Digital Threats: Research and Practice, 9(4),

It is difficult to discern real-world consequences of attacks on an enterprise when investigating network-centric data alone. In recent years, many tools have been developed to help understand attacks using visualization, but few aim to predict real-... Read More about Assessing a decision support tool for SOC analysts.

A review of learning theories and models underpinning technology-enhanced learning artefacts (2020)
Journal Article
Hammad, R., Khan, Z., Safieddine, F., & Ahmed, A. (2020). A review of learning theories and models underpinning technology-enhanced learning artefacts. World Journal of Science, Technology and Sustainable Development, 17(4), 341-354. https://doi.org/10.1108/WJSTSD-06-2020-0062

Purpose – Various technology-enhanced learning software and tools exist where technology becomes the main driver for these developments at the expense of pedagogy. The literature reveals the missing balance between technology and pedagogy in the cont... Read More about A review of learning theories and models underpinning technology-enhanced learning artefacts.

Secure and communications-efficient collaborative prognosis (2020)
Journal Article
Dhada, M., Jain, A., Herrera, M., Hernandez, M. P., & Parlikad, A. (2020). Secure and communications-efficient collaborative prognosis. IET Collaborative Intelligent Manufacturing, 2(4), 164-173. https://doi.org/10.1049/iet-cim.2020.0035

Collaborative prognosis is a technique that is used to enable assets to improve their ability to predict failures by learning from the failures of similar other assets. This is typically made possible by enabling the assets to communicate with each o... Read More about Secure and communications-efficient collaborative prognosis.

Max-gain relay selection scheme for wireless networks (2020)
Journal Article
Ullah, S., Malik, M. H., Tuysuz, M. F., Hasnain, M., & Aydin, M. E. (2021). Max-gain relay selection scheme for wireless networks. International Journal of Engineering Science and Technology, 24(1), 183-191. https://doi.org/10.1016/j.jestch.2020.08.009

© 2020 Karabuk University Next generation wireless systems are supposed to handle high amount of data with broader coverage and high quality of service (QoS). When a signal travels from a source to destination, the signal quality may suffer from the... Read More about Max-gain relay selection scheme for wireless networks.

A two-phase anomaly detection model for secure intelligent transportation ride-hailing trajectories (2020)
Journal Article
Belhadi, A., Djenouri, Y., Srivastava, G., Djenouri, D., Cano, A., & Lin, J. C. W. (2021). A two-phase anomaly detection model for secure intelligent transportation ride-hailing trajectories. IEEE Transactions on Intelligent Transportation Systems, 22(7), 4496-4506. https://doi.org/10.1109/tits.2020.3022612

This paper addresses the taxi fraud problem and introduces a new solution to identify trajectory outliers. The approach as presented allows to identify both individual and group outliers and is based on a two phase-based algorithm. The first phase de... Read More about A two-phase anomaly detection model for secure intelligent transportation ride-hailing trajectories.

Deep learning for pedestrian collective behavior analysis in smart cities: A model of group trajectory outlier detection (2020)
Journal Article
Belhadi, A., Djenouri, Y., Srivastava, G., Djenouri, D., Lin, J. C., & Fortino, G. (2021). Deep learning for pedestrian collective behavior analysis in smart cities: A model of group trajectory outlier detection. Information Fusion, 65, 13-20. https://doi.org/10.1016/j.inffus.2020.08.003

This paper introduces a new model to identify collective abnormal human behaviors from large pedestrian data in smart cities. To accurately solve the problem, several algorithms have been proposed in this paper. These can be split into two categories... Read More about Deep learning for pedestrian collective behavior analysis in smart cities: A model of group trajectory outlier detection.

Wearable sensor-based human activity recognition using hybrid deep learning techniques (2020)
Journal Article
Wang, H., Zhao, J., Li, J., Tian, L., Tu, P., Cao, T., …Li, S. (2020). Wearable sensor-based human activity recognition using hybrid deep learning techniques. Security and Communication Networks, 2020, Article 2132138. https://doi.org/10.1155/2020/2132138

Human activity recognition (HAR) can be exploited to great benefits in many applications, including elder care, health care, rehabilitation, entertainment, and monitoring. Many existing techniques, such as deep learning, have been developed for speci... Read More about Wearable sensor-based human activity recognition using hybrid deep learning techniques.

Per-pixel classification of clouds from whole sky HDR images (2020)
Journal Article
Satilmis, P., Bashford-Rogers, T., Chalmers, A., & Debattista, K. (2020). Per-pixel classification of clouds from whole sky HDR images. Signal Processing: Image Communication, 88, Article 115950. https://doi.org/10.1016/j.image.2020.115950

© 2020 Elsevier B.V. Accurately identifying cloud types in images has multiple uses from meteorological science to computer graphics, especially as clouds are a major factor influencing atmospheric radiative transport. Understanding which cloud types... Read More about Per-pixel classification of clouds from whole sky HDR images.