Synthetic Biology Open Language (SBOL) Version 2.3. (2019)
Journal Article
Misirli. (2019). Synthetic Biology Open Language (SBOL) Version 2.3. Journal of Integrative Bioinformatics, https://doi.org/10.1515/jib-2019-0025

Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long... Read More about Synthetic Biology Open Language (SBOL) Version 2.3..

User Perception of Bitcoin Usability and Security across Novice Users (2019)
Journal Article
(2019). User Perception of Bitcoin Usability and Security across Novice Users. International Journal of Human-Computer Studies, 94-100. https://doi.org/10.1016/j.ijhcs.2019.02.004

This paper investigates users’ perceptions and experiences of an anonymous digital payment system (Bitcoin) and its influence on users in terms of usability and security in comparison to other non-anonymous payment systems such as credit/debit cards.... Read More about User Perception of Bitcoin Usability and Security across Novice Users.

Maximum Individual Complexity is Indefinitely Scalable in Geb (2019)
Journal Article
Channon. (2019). Maximum Individual Complexity is Indefinitely Scalable in Geb. Artificial Life, 134-144. https://doi.org/10.1162/artl_a_00285

Geb was the first artificial life system to be classified as exhibiting open-ended evolutionary dynamics according to Bedau and Packard’s evolutionary activity measures and is the only one to have been classified as such according to the enhanced ver... Read More about Maximum Individual Complexity is Indefinitely Scalable in Geb.

Maximum Individual Complexity is Indefinitely Scalable in Geb (2019)
Journal Article
Channon. (2019). Maximum Individual Complexity is Indefinitely Scalable in Geb. Artificial Life, 134-144. https://doi.org/10.1162/artl_a_00285

Geb was the first artificial life system to be classified as exhibiting open-ended evolutionary dynamics according to Bedau and Packard’s evolutionary activity measures and is the only one to have been classified as such according to the enhanced ve... Read More about Maximum Individual Complexity is Indefinitely Scalable in Geb.

Artificial Intelligence in Clinical Decision Support: Challenges for Evaluating AI and Practical Implications (2019)
Journal Article
(2019). Artificial Intelligence in Clinical Decision Support: Challenges for Evaluating AI and Practical Implications. https://doi.org/10.1055/s-0039-1677903

OBJECTIVES
This paper draws attention to: i) key considerations for evaluating artificial intelligence (AI) enabled clinical decision support; and ii) challenges and practical implications of AI design, development, selection, use, and ongoing surve... Read More about Artificial Intelligence in Clinical Decision Support: Challenges for Evaluating AI and Practical Implications.

Receiver Design Using Genetic Circuits in Molecular Communication (2019)
Presentation / Conference
Misirli. (2019, April). Receiver Design Using Genetic Circuits in Molecular Communication. Presented at 4th workshop on Molecular Communications, Linz, Austria

Understanding the dynamics of molecular communications between cells and intracellular response is crucial to create predictable cellular applications. When the propagation mechanism is diffusion based, the arrival histogram of molecules becomes heav... Read More about Receiver Design Using Genetic Circuits in Molecular Communication.

Deep Convolutional Generative Adversarial Network-Based Food Recognition Using Partially Labeled Data (2019)
Journal Article
Mandal, B., Puhan, N. B., & Verma, A. (2019). Deep Convolutional Generative Adversarial Network-Based Food Recognition Using Partially Labeled Data. IEEE Sensors Letters, 3(2), Article ARTN 7000104. https://doi.org/10.1109/LSENS.2018.2886427

Traditional machine learning algorithms using hand-crafted feature extraction techniques (such as local binary pattern) have limited accuracy because of high variation in images of the same class (or intraclass variation) for food recognition tasks.... Read More about Deep Convolutional Generative Adversarial Network-Based Food Recognition Using Partially Labeled Data.

Problems with Statistical Practice in Software Engineering Research (2019)
Conference Proceeding
Kitchenham, B., Madeyski, L., & Brereton, P. (2019). Problems with Statistical Practice in Software Engineering Research. In EASE '19 Proceedings of the Evaluation and Assessment on Software Engineering (134-143). https://doi.org/10.1145/3319008.3319009

Background
Examples of questionable statistical practice, when published in high quality software engineering (SE) journals, may lead to novice researchers adopting incorrect statistical practices.

Objective
Our goal is to highlight issues contr... Read More about Problems with Statistical Practice in Software Engineering Research.

Measuring and Testing the Scalability of Cloud-based Software Services (2019)
Conference Proceeding
Al-Said Ahmad, A., & Andras, P. (2019). Measuring and Testing the Scalability of Cloud-based Software Services. In 2018 Fifth International Symposium on Innovation in Information and Communication Technology (ISIICT) (67-74). https://doi.org/10.1109/ISIICT.2018.8613297

Performance and scalability testing and measurements of cloud-based software services are critically important in the context of rapid growth of cloud computing and supporting the delivery of these services. Cloud-based software services performance... Read More about Measuring and Testing the Scalability of Cloud-based Software Services.

Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile (2019)
Journal Article
MacCormick, I. J., Williams, B. M., Zheng, Y., Li, K., Al-Bander, B., Czanner, S., …Czanner, G. (2019). Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile. PloS one, 14(1), e0209409 - e0209409. https://doi.org/10.1371/journal.pone.0209409

Glaucoma is the leading cause of irreversible blindness worldwide. It is a heterogeneous group of conditions with a common optic neuropathy and associated loss of peripheral vision. Both over and under-diagnosis carry high costs in terms of healthcar... Read More about Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile.

An evaluation model for information security strategies in healthcare data systems (2018)
Thesis
Almutiq, M. M. (2018). An evaluation model for information security strategies in healthcare data systems. (Thesis). Keele University. Retrieved from https://keele-repository.worktribe.com/output/412314

This thesis presents a newly developed evaluation model, EMISHD (An "Evaluation Model for Information Security Strategies in Healthcare Data Systems") which can address the specific requirements of information security in healthcare sector. Based on... Read More about An evaluation model for information security strategies in healthcare data systems.

Detection of suspicious URLs in online social networks using supervised machine learning algorithms (2018)
Thesis
Al-Janabi, M. F. Z. (2018). Detection of suspicious URLs in online social networks using supervised machine learning algorithms. (Thesis). Keele University. Retrieved from https://keele-repository.worktribe.com/output/412294

This thesis proposes the use of several supervised machine learning classification models that were built to detect the distribution of malicious content in OSNs. The main focus was on ensemble learning algorithms such as Random Forest, gradient boos... Read More about Detection of suspicious URLs in online social networks using supervised machine learning algorithms.

Trusting Intelligent Machines (2018)
Journal Article
(2018). Trusting Intelligent Machines. https://doi.org/10.1109/mts.2018.2876107

Intelligent machines have reached capabilities that go beyond a level that a human being can fully comprehend without sufficiently detailed understanding of the underlying mechanisms. The choice of moves in the game Go (generated by Deep Mind?s Alpha... Read More about Trusting Intelligent Machines.

A Genetic Circuit Compiler: Generating Combinatorial Genetic Circuits with Web Semantics and Inference (2018)
Journal Article
Misirli. (2018). A Genetic Circuit Compiler: Generating Combinatorial Genetic Circuits with Web Semantics and Inference. ACS synthetic biology, 2812-2823. https://doi.org/10.1021/acssynbio.8b00201

A central strategy of synthetic biology is to understand the basic processes of living creatures through engineering organisms using the same building blocks. Biological machines described in terms of parts can be studied by computer simulation in an... Read More about A Genetic Circuit Compiler: Generating Combinatorial Genetic Circuits with Web Semantics and Inference.

Harmonizing semantic annotations for computational models in biology (2018)
Journal Article
Misirli. (2018). Harmonizing semantic annotations for computational models in biology. Briefings in bioinformatics, bby087 - bby087. https://doi.org/10.1093/bib/bby087

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for... Read More about Harmonizing semantic annotations for computational models in biology.

Student Centred Design of a Learning Analytics System (2018)
Conference Proceeding
De Quincey, E., Briggs, C., Kyriacou, T., & Waller, R. (2018). Student Centred Design of a Learning Analytics System. In LAK19: Proceedings of the 9th International Conference on Learning Analytics & Knowledge. https://doi.org/10.1145/3303772.3303793

Current Learning Analytics (LA) systems are primarily designed with University staff members as the target audience; very few are aimed at students, with almost none being developed with direct student involvement and undertaking a comprehensive eval... Read More about Student Centred Design of a Learning Analytics System.

The Usability of E-learning Platforms in Higher Education: A Systematic Mapping Study (2018)
Conference Proceeding
Abuhlfaia, K., & de Quincey, E. (2018). The Usability of E-learning Platforms in Higher Education: A Systematic Mapping Study. . https://doi.org/10.14236/ewic/HCI2018.7

The use of e-learning in higher education has increased significantly in recent years, which has led to several studies being conducted to investigate the usability of the platforms that support it. A variety of different usability evaluation methods... Read More about The Usability of E-learning Platforms in Higher Education: A Systematic Mapping Study.

Deep Adaptive Temporal Pooling for Activity Recognition (2018)
Conference Proceeding
Song, S., Cheung, N., Chandrasekhar, V., & Mandal, B. (2018). Deep Adaptive Temporal Pooling for Activity Recognition. . https://doi.org/10.1145/3240508.3240713

Deep neural networks have recently achieved competitive accuracy for human activity recognition. However, there is room for improvement, especially in modeling of long-term temporal importance and determining the activity relevance of different tempo... Read More about Deep Adaptive Temporal Pooling for Activity Recognition.

Fault Detection in Steel-Reinforced Concrete Using Echo State Networks (2018)
Conference Proceeding
Wootton, A. J., Day, C. R., & Haycock, P. W. (2018). Fault Detection in Steel-Reinforced Concrete Using Echo State Networks. In 2018 International Joint Conference on Neural Networks (IJCNN) (1-8). https://doi.org/10.1109/IJCNN.2018.8489761

The cost of maintaining and repairing the world's ageing reinforced concrete infrastructure continues to increase, and is expected to cost the United States economy alone $58 billion by 2020. Consequently, the use of non-destructive testing technolog... Read More about Fault Detection in Steel-Reinforced Concrete Using Echo State Networks.

Social Learning in Repeated Cooperation Games in Uncertain Environments (2018)
Journal Article
(2018). Social Learning in Repeated Cooperation Games in Uncertain Environments. Cognitive Systems Research, 24-39. https://doi.org/10.1016/j.cogsys.2018.04.013

Cooperation and social learning are fundamental mechanisms that maintain social organisation among animals and humans. Social institutions can be conceptualised abstractly as cooperation games with social learning. In some ca ses potential cooperatio... Read More about Social Learning in Repeated Cooperation Games in Uncertain Environments.