dotLAB BRAZIL
dotLAB Brazil is one of IIDB’s longest collaborations. Led by Prof. Patricia Endo at the Universidade de Pernambuco, dotLAB Brazil coordinates collaborations between IIDB and researchers from Universidade Federal de Pernambuco, Universidade Federal do Rio Grande do Norte, Universidade Federal da Paraíba, the Instituto Todos pela Saúde, and Fund de Medicina Tropical Dr Heitor Vieira Dourado. A significant focus of the collaboration is the application of machine learning and deep learning techniques for improved decision-making and process, network, and service optimisation.
RESEARCH PROJECTS
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Health Informatics and Information Systems
P. Endo (UPE), V. Sampaio (ITpS), T. Lynn (DCU), G. Leoni (DCU), G. Fox (DCU), L. van der Werff (DCU), P. Rosati (University of Galway)
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Hate Speech & Misinformation on Social Media
P. Endo (UPE), T. Lynn (DCU), G. Leoni (DCU), A. Egli (DCU), G. Sinclair (DCU), P. Rosati (University of Galway)
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Sustainable Decision Making
P. Endo (UPE), A. Ribeiro (UFPE), T. Lynn (DCU), P. Rosati (University of Galway)
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Service and Network Optimisation and Visualisation
P. Endo (UPE), J. Kelner (UFPE), D. Sadok (UFPE), I. Silva (UFRN), C. Morais (UFPB), T. Lynn (DCU), G. Leoni (DCU)
SELECTED RESEARCH PUBLICATIONS
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A Brazilian Classified Data Set for Prognosis of Tuberculosis, between January 2001 and April 2020
Lino Ferreira da Silva Barros, M.H., Santos, G.L., de Almeida Rodrigues, M.G., Sampaio, V., Lynn, T. and Endo, P.T., 2022. A Brazilian classified data set for prognosis of tuberculosis, between January 2001 and April 2020. Scientific Data, 9(1), p.771.
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A Reinforcement Learning-Based Approach for Availability-Aware Service Function Chain Placement in Large-Scale Networks
Santos, G.L., Endo, P.T., Lynn, T., Sadok, D. and Kelner, J., 2022. A reinforcement learning-based approach for availability-aware service function chain placement in large-scale networks. Future Generation Computer Systems, 136, pp.93-109.
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Arboviral Disease Record Data-Dengue and Chikungunya, Brazil, 2013–2020
da Silva Neto, S.R., Tabosa de Oliveira, T., Teixiera, I.V., Medeiros Neto, L., Souza Sampaio, V., Lynn, T. and Endo, P.T., 2022. Arboviral disease record data-dengue and chikungunya, brazil, 2013–2020. Scientific Data, 9(1), p.198.
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Prediction of Malaria using Deep Learning Models: A Case Study on City Clusters in the State of Amazonas, Brazil, from 2003 to 2018
Barboza, M.F.X., Monteiro, K.H.D.C., Rodrigues, I.R., Santos, G.L., Monteiro, W.M., Figueira, E.A.G., Sampaio, V.D.S., Lynn, T. and Endo, P.T., 2022. Prediction of malaria using deep learning models: A case study on city clusters in the state of Amazonas, Brazil, from 2003 to 2018. Revista da Sociedade Brasileira de Medicina Tropical, 55.
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Illusion of Truth: Analysing and Classifying COVID-19 Fake News in Brazilian Portuguese Language
Endo, P.T., Santos, G.L., de Lima Xavier, M.E., Nascimento Campos, G.R., de Lima, L.C., Silva, I., Egli, A. and Lynn, T., 2022. Illusion of Truth: Analysing and classifying COVID-19 fake news in Brazilian Portuguese language. Big Data and Cognitive Computing, 6(2), p.36.
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Short-and Very Short-Term Firm-Level Load Forecasting for Warehouses: A Comparison of Machine Learning and Deep Learning Models
Ribeiro, A.M.N., do Carmo, P.R.X., Endo, P.T., Rosati, P. and Lynn, T., 2022. Short-and very short-term firm-level load forecasting for warehouses: a comparison of machine learning and deep learning models. Energies, 15(3), p.750.
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Examining the Determinants of Acceptance and Use of Mobile Contact Tracing Applications in Brazil: An Extended Privacy Calculus Perspective
Fox, G., van der Werff, L., Rosati, P., Takako Endo, P. and Lynn, T., 2022. Examining the determinants of acceptance and use of mobile contact tracing applications in Brazil: An extended privacy calculus perspective. Journal of the Association for Information Science and Technology, 73(7), pp.944-967.
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Predicting Short-Term Mobile Internet Traffic from Internet Activity using Recurrent Neural Networks
Santos, G.L., Rosati, P., Lynn, T., Kelner, J., Sadok, D. and Endo, P.T., 2022. Predicting short-term mobile Internet traffic from Internet activity using recurrent neural networks. International Journal of Network Management, 32(3), p.e2191.
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Maximising the Availability of an Internet of Medical Things System using Surrogate Models and Nature-Inspired Approaches
Santos, G.L., Gomes, D., Silva, F.A., Endo, P.T. and Lynn, T., 2022. Maximising the availability of an internet of medical things system using surrogate models and nature-inspired approaches. International Journal of Grid and Utility Computing, 13(2-3), pp.291-308.
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Availability-Aware and Energy-Aware Dynamic SFC Placement using Reinforcement Learning
Santos, G.L., Lynn, T., Kelner, J. and Endo, P.T., 2021. Availability-aware and energy-aware dynamic SFC placement using reinforcement learning. The Journal of Supercomputing, pp.1-30.
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Benchmarking of Machine Learning Models to Assist the Prognosis of Tuberculosis
da Silva Rocha, É., Lorenzato de Oliveira, J.F., Lynn, T., Sampaio, V. and Endo, P.T., 2021. Benchmarking of Machine Learning Models to Assist the Prognosis of Tuberculosis.
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Synthetic Image Generation for Training Deep Learning-Based Automated License Plate Recognition Systems on the Brazilian Mercosur Standard
Silvano, G., Ribeiro, V., Greati, V., Bezerra, A., Silva, I., Endo, P.T. and Lynn, T., 2021. Synthetic image generation for training deep learning-based automated license plate recognition systems on the Brazilian Mercosur standard. Design Automation for Embedded Systems, 25, pp.113-133.
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Automating the Service Function Chain Availability Assessment
Santos, G.L., Endo, P.T., Lynn, T., Sadok, D. and Kelner, J., 2021, September. Automating the service function chain availability assessment. In 2021 IEEE Symposium on Computers and Communications (ISCC) (pp. 1-7). IEEE.
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Simulating and Evaluating a Real-World ElasticSearch System Using the RECAP DES Simulator
Bendechache, M., Svorobej, S., Endo, P.T., Mihai, A. and Lynn, T., 2021. Simulating and Evaluating a Real-World ElasticSearch System Using the RECAP DES Simulator. Future Internet, 13(4), p.83.
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Artificial Mercosur License Plates Dataset
Silvano, G.V.T., Silva, I., Ribeiro, V.C.T., Greati, V.R., Bezerra, A., Endo, P.T. and Lynn, T., 2020. Artificial Mercosur license plates dataset. Data in Brief, 33, p.106554.
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Sorting the Healthy Diet Signal from the Social Media Expert Noise: Preliminary Evidence from the Healthy Diet Discourse on Twitter
Lynn, T., Rosati, P., Leoni Santos, G. and Endo, P.T., 2020. Sorting the healthy diet signal from the social media expert noise: preliminary evidence from the healthy diet discourse on Twitter. International Journal of Environmental Research and Public Health, 17(22), p.8557.
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Short-Term Firm-Level Energy-Consumption Forecasting for Energy-Intensive Manufacturing: A Comparison of Machine Learning and Deep Learning Models
Ribeiro, A.M.N., do Carmo, P.R.X., Rodrigues, I.R., Sadok, D., Lynn, T. and Endo, P.T., 2020. Short-term firm-level energy-consumption forecasting for energy-intensive manufacturing: a comparison of machine learning and deep learning models. Algorithms, 13(11), p.274.
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The Cloud-to-Thing Continuum: Opportunities and Challenges in Cloud, Fog and Edge Computing
Lynn, T., Mooney, J.G., Lee, B. and Endo, P.T., 2020. The cloud-to-thing continuum: opportunities and challenges in cloud, fog and edge computing. Palgrave-Macmillan.
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The Internet of Things: Definitions, Key Concepts, and Reference Architectures
Lynn, T., Endo, P.T., Ribeiro, A.M.N., Barbosa, G.B. and Rosati, P., 2020. The internet of things: definitions, key concepts, and reference architectures. The Cloud-To-Thing Continuum: Opportunities and Challenges in Cloud, Fog and Edge Computing, pp.1-22.
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The Internet of Things for Healthcare: Optimising e-Health System Availability in the Fog and Cloud
Santos, G.L., Gomes, D., Kelner, J., Sadok, D., Silva, F.A., Endo, P.T. and Lynn, T., 2020. The internet of things for healthcare: Optimising e-health system availability in the fog and cloud. International Journal of Computational Science and Engineering, 21(4), pp.615-628.
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Towards Simulation and Optimization of Cache Placement on Large Virtual Content Distribution Networks
Filelis-Papadopoulos, C.K., Endo, P.T., Bendechache, M., Svorobej, S., Giannoutakis, K.M., Gravvanis, G.A., Tzovaras, D., Byrne, J. and Lynn, T., 2020. Towards simulation and optimization of cache placement on large virtual content distribution networks. Journal of Computational Science, 39, p.101052.
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Simulating Resource Management across the Cloud-to-Thing Continuum: A Survey and Future Directions
Bendechache, M., Svorobej, S., Takako Endo, P. and Lynn, T., 2020. Simulating resource management across the cloud-to-thing continuum: A survey and future directions. Future Internet, 12(6), p.95.
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#StayHome: Monitoring and Benchmarking Social Isolation Trends in Caruaru and the Região Metropolitana do Recife during the COVID-19 Pandemic
Endo, P.T., Silva, I., Lima, L., Bezerra, L., Gomes, R., Ribeiro-Dantas, M., Alves, G., Monteiro, K.H.D.C., Lynn, T. and Sampaio, V.D.S., 2020. #StayHome: Monitoring and benchmarking social isolation trends in Caruaru and the Região Metropolitana do Recife during the COVID-19 pandemic. Revista da Sociedade Brasileira de Medicina Tropical, 53.
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Accelerometer-Based Human Fall Detection using Convolutional Neural Networks
Santos, G.L., Endo, P.T., Monteiro, K.H.D.C., Rocha, E.D.S., Silva, I. and Lynn, T., 2019. Accelerometer-based human fall detection using convolutional neural networks. Sensors, 19(7), p.1644.
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Optimizing Resource Availability in Composable Data Center Infrastructures
Ferreira, L., da Silva Rocha, E., Monteiro, K.H.C., Santos, G.L., Silva, F.A., Kelner, J., Sadok, D., Bastos Filho, C.J., Rosati, P., Lynn, T. and Endo, P.T., 2019, November. Optimizing resource availability in composable data center infrastructures. In 2019 9th Latin-American Symposium on Dependable Computing (LADC) (pp. 1-10). IEEE.
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Integrating IoT+ Fog+ Cloud Infrastructures: System Modelling and Research Challenges
Santos, G.L., Ferreira, M., Ferreira, L., Kelner, J., Sadok, D., Albuquerque, E., Lynn, T. and Endo, P.T., 2019. Integrating iot+ fog+ cloud infrastructures: System modeling and research challenges. Fog and Edge Computing: Principles and Paradigms, pp.51-78.
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Data Set for Automatic Detection of Online Misogynistic Speech
Lynn, T., Endo, P.T., Rosati, P., Silva, I., Santos, G.L. and Ging, D., 2019. Data set for automatic detection of online misogynistic speech. Data in brief, 26.
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Simulating Large vCDN Networks: A Parallel Approach
Filelis-Papadopoulos, C.K., Giannoutakis, K.M., Gravvanis, G.A., Endo, P.T., Tzovaras, D., Svorobej, S. and Lynn, T., 2019. Simulating large vCDN networks: A parallel approach. Simulation Modelling Practice and Theory, 92, pp.100-114.
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A Preliminary Exploration of Uber Data as an Indicator of Urban Liveability
Bezerra, A., Alves, G., Silva, I., Rosati, P., Endo, P.T. and Lynn, T., 2019, June. A preliminary exploration of uber data as an indicator of urban liveability. In 2019 International Conference on Cyber Situational Awareness, Data Analytics And Assessment (Cyber SA) (pp. 1-8). IEEE.
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Simulating Fog and Edge Computing Scenarios: An Overview and Research Challenges
Svorobej, S., Endo, P.T., Bendechache, M., Filelis-Papadopoulos, C., Giannoutakis, K.M., Gravvanis, G.A., Tzovaras, D., Byrne, J. and Lynn, T., 2019. Simulating fog and edge computing scenarios: An overview and research challenges. Future Internet, 11(3), p.55.
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Analyzing the Availability and Performance of an e-Health System Integrated with Edge, Fog, and Cloud Infrastructures
Santos, G.L., Takako Endo, P., Ferreira da Silva Lisboa Tigre, M.F., Ferreira da Silva, L.G., Sadok, D., Kelner, J. and Lynn, T., 2018. Analyzing the availability and performance of an e-health system integrated with edge, fog and cloud infrastructures. Journal of Cloud Computing, 7(1), pp.1-22.
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SiMoNa: A Proof-of-Concept Domain Specific Modelling Language for IoT Infographics
De Morais, C.M., Kelner, J., Sadok, D. and Lynn, T., 2018, October. SiMoNa: A proof-of-concept domain specific modeling language for IoT infographics. In 2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) (pp. 199-203). IEEE.
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Modeling the Availability of an e-Health System Integrated with Edge, Fog and Cloud Infrastructures
da Silva Lisboa, M.F.F., Santos, G.L., Lynn, T., Sadok, D., Kelner, J. and Endo, P.T., 2018, June. Modeling the availability of an e-health system integrated with edge, fog and cloud infrastructures. In 2018 IEEE symposium on computers and communications (ISCC) (pp. 00416-00421). IEEE.
GET IN TOUCH
Prof Theo
LynnFull Professor,
DCU
Prof Patricia
Takako EndoFull Professor, Universidade de Pernambuco