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Generative modeling of synthetic eye-tracking data: NLP-based approach with recurrent neural networks (2020)
Conference Proceeding
Elbattah, M., Guérin, J., Carette, R., Cilia, F., & Dequen, G. (2020). Generative modeling of synthetic eye-tracking data: NLP-based approach with recurrent neural networks. In Proceedings of the 12th International Joint Conference on Computational Intelligence (479-484). https://doi.org/10.5220/0010177204790484

This study explores a Machine Learning-based approach for generating synthetic eye-tracking data. In this respect, a novel application of Recurrent Neural Networks is experimented. Our approach is based on learning the sequence patterns of eye-tracki... Read More about Generative modeling of synthetic eye-tracking data: NLP-based approach with recurrent neural networks.

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.

Comparing agent-based control architectures for next generation telecommunication network infrastructures (2020)
Journal Article
Perez Hernandez, M., McFarlane, D., Herrera, M., Jain, A. K., & Parlikad, A. K. (2020). Comparing agent-based control architectures for next generation telecommunication network infrastructures. IFAC-PapersOnLine, 53(2), 11062-11067. https://doi.org/10.1016/j.ifacol.2020.12.238

Multi-agent systems have been an effective choice for designing control systems that are flexible and agile. However, few attention has been given to the evaluation of the architectures of such systems. This becomes critical with the emerging require... Read More about Comparing agent-based control architectures for next generation telecommunication network infrastructures.

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.

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.

Audio Anywhere with Faust (2020)
Conference Proceeding
Gaster, B. R., & Cole, M. (2020). Audio Anywhere with Faust.

This paper introduces \emph{Audio Anywhere} (\emph{AA}), a framework for working with audio plugins that are compiled once and run anywhere. At the heart of Audio Anywhere is an audio engine whose Digital Signal Processing (DSP) components are writte... Read More about Audio Anywhere with Faust.

A focus on codemixing and codeswitching in Tamil speech to text (2020)
Conference Proceeding
Navaladi, L., Gandhi, I., Ofei, W., Chiurunga, Z., Mashat, A., Basandrai, A., …Ramachandran, R. (in press). A focus on codemixing and codeswitching in Tamil speech to text. In 2020 8th International Conference in Software Engineering Research and Innovation (CONISOFT) (154-165). https://doi.org/10.1109/CONISOFT50191.2020.00031

This paper attempts to develop an application that converts Tamil language speech to Tamil text, with a view to encourage usage and indirectly ensure linguistic preservation of a classical language. The application converts spoken Tamil to text witho... Read More about A focus on codemixing and codeswitching in Tamil speech to text.

Covid-19 Care – A mobile application to help connect volunteers and vulnerable people in the community during the Covid-19 lockdown (2020)
Conference Proceeding
Ogunshile, E., Phung, K., & Odongo, S. (in press). Covid-19 Care – A mobile application to help connect volunteers and vulnerable people in the community during the Covid-19 lockdown. In 2020 8th International Conference in Software Engineering Research and Innovation (CONISOFT) (124-133). https://doi.org/10.1109/CONISOFT50191.2020.00027

Whenever the world is faced with a devastating outbreak of events, technology innovations have proven to be a go to solution that expedite the recovery process. We propose a mobile application rapidly developed as a contender to the TechForce19 innov... Read More about Covid-19 Care – A mobile application to help connect volunteers and vulnerable people in the community during the Covid-19 lockdown.

An algorithm for implementing a minimal stream X-Machine model to test the correctness of a system (2020)
Conference Proceeding
Ogunshile, E., & Phung, K. (in press). An algorithm for implementing a minimal stream X-Machine model to test the correctness of a system. In 2020 8th International Conference in Software Engineering Research and Innovation (CONISOFT). https://doi.org/10.1109/CONISOFT50191.2020.00023

The rapid change of requirements has made software more complex and harder to maintain. Software testing tools play an important role in the Software Development Life Cycle. However, many technology companies have employed fast paced development of s... Read More about An algorithm for implementing a minimal stream X-Machine model to test the correctness of a system.

UAV’s applications, architecture, security issues and attack scenarios: A survey (2020)
Book Chapter
Khan, N. A., Brohi, S., & Jhanjhi, N. (2020). UAV’s applications, architecture, security issues and attack scenarios: A survey. In S. Peng, L. H. Son, G. Suseendran, & D. Balaganesh (Eds.), Book cover Book cover Intelligent Computing and Innovation on Data Science (753-760). Online and in print.: Springer. https://doi.org/10.1007/978-981-15-3284-9_81

Unmanned aerial vehicles (UAVs)/drones have become very popular in recent years as they are widely used in several domains. They are widely used in both military and civilian applications such as aerial photography, entertainment, search and rescue m... Read More about UAV’s applications, architecture, security issues and attack scenarios: A survey.

Multi-channel ConvNet approach to predict the risk of in-hospital mortality for ICU patients (2020)
Conference Proceeding
Viton, F., Elbattah, M., Guérin, J., & Dequen, G. (2020). Multi-channel ConvNet approach to predict the risk of in-hospital mortality for ICU patients. In Proceedings of the 1st International Conference on Deep Learning Theory and Applications (98-102). https://doi.org/10.5220/0009891900980102

The healthcare arena has been undergoing impressive transformations thanks to advances in the capacity to capture, store, process, and learn from data. This paper re-visits the problem of predicting the risk of in-hospital mortality based on Time Ser... Read More about Multi-channel ConvNet approach to predict the risk of in-hospital mortality for ICU patients.

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.

Deep learning to predict hospitalization at triage: Integration of structured data and unstructured text (2020)
Conference Proceeding
Arnaud, E., Elbattah, M., Gignon, M., & Dequen, G. (2020). Deep learning to predict hospitalization at triage: Integration of structured data and unstructured text. In 2020 IEEE International Conference on Big Data (Big Data) (4836-4841). https://doi.org/10.1109/bigdata50022.2020.9378073

Overcrowding in Emergency Departments (ED) is considered as an international issue, which could have adverse impacts on multiple care outcomes such as the length of stay for example. Part of the solution could lie in the early prediction of the patie... Read More about Deep learning to predict hospitalization at triage: Integration of structured data and unstructured text.

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.

Using active learning to understand the videoconference experience: A case study (2020)
Conference Proceeding
Llewellyn, S., Simons, C., & Smith, J. (2020). Using active learning to understand the videoconference experience: A case study. https://doi.org/10.1007/978-3-030-63799-6_30

Videoconferencing is becoming ubiquitous, especially so during the COVID-19 pandemic. However, user experience of a videoconference call can be variable. To better understand and classify the performance of videoconference call systems, this paper re... Read More about Using active learning to understand the videoconference experience: A case study.

A mixture-of-experts model for learning multi-facet entity embeddings (2020)
Conference Proceeding
Alshaikh, R., Bouraoui, Z., Jeawak, S., & Schockaert, S. (2020). A mixture-of-experts model for learning multi-facet entity embeddings. In Proceedings of the 28th International Conference on Computational Linguistics (5124-5135)

Various methods have already been proposed for learning entity embeddings from text descriptions. Such embeddings are commonly used for inferring properties of entities, for recommendation and entity-oriented search, and for injecting background know... Read More about A mixture-of-experts model for learning multi-facet entity embeddings.

NLP-based approach to detect autism spectrum disorder in saccadic eye movement (2020)
Conference Proceeding
Elbattah, M., Guerin, J. L., Carette, R., Cilia, F., & Dequen, G. (2020). NLP-based approach to detect autism spectrum disorder in saccadic eye movement. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI) (1581-1587). https://doi.org/10.1109/ssci47803.2020.9308238

Autism Spectrum Disorder (ASD) is a lifelong condition generally characterized by social and communication impairments. The early diagnosis of ASD is highly desirable, yet it could be complicated by several factors. Standard tests typically require i... Read More about NLP-based approach to detect autism spectrum disorder in saccadic eye movement.