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Manju Lasantha Fernando
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Posts
Connecting to Checkpoint Gateway with Openswan - The details
Published:
In a previous post I explained the basic pre-requisites that you have to setup before you try to establish a VPN tunnel with Openswan. Also, I tried to explain some related terminology to the best of my understanding (That ‘to the best of my understanding’ part is important … :-) ). In this post, the detailed configuration that worked for me is given.
VPN Tuneel to Checkpoint Gateway with Openswan - Intro
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Recently I had the situation where I had to connect to a VPN via a Checkpoint Security Gateway (R70.x) via Linux with IPSec stack. While there were a lot of posts in the net regarding Openswan to which I am very grateful, I still had to tweak configurations from here and there until I could get it working with collaboration from the admin at the gateway side as well. There is also this great book called ‘Building and Integrating Virtual Private Networks with Openswan’ by Ken Bantoft and Paul Wouters which is like the recommended text for Openswan stuff. For Openswan, this is the background you need for get it working.
Of Anime and Others
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I like anime very much. Why? Because of those beautifully drawn characters and landscapes? Definitely. But, ….. in reality, I consider some of those great anime series and films to be beautiful pieces of art. They discuss something more than what is shown in the surface. Something relevant, a social issue, timely or something that is thought provoking. This is true of any great piece of art, irrespective of form or media. It gives the audience something more to think about than just what its outside appearance is.
Brazil exits FIFA 2010
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Indeed it broke the hearts of many Brazilian fans to see their team exit the soccer world cup finals at the quarter final stages. Brazil were among the tournament favourites from the very beginning and even thought Netherlands was a tough team to compete with, no one could say today’s match was an upset result.
publications
Impact of Human Mobility on Spread of Dengue in Sri Lanka
Published in Milan, Italy, 2017
Human mobility plays a significant role in spatio-temporal propagation of infectious diseases. But how much of an impact does human mobility have on propagating a dengue outbreak in a dengue endemic country such as Sri Lanka?
Recommended citation: Fernando, L., Perera, A. S., Lokanathan, S., Ghouse, A., & Tissera, H. (2017). Impact of Human Mobility on Spread of Dengue in Sri Lanka. In Book of Abstracts (Oral) of 5th International Conference on Scientific Analysis of Mobile Phone datasets (NetMob) (pp. 75–77). Milan, Italy http://lasanthafdo.github.io/files/netmob-cdr-dengue.pdf
Predictive model for the dengue incidences in Sri Lanka using mobile network big data
Published in Kandy, Sri Lanka, 2017
Multiple studies in recent literature have shown that human mobility has a considerable effect on the importation of dengue to an immunologically dengue ‘naive’ regions. The purpose of this study is to validate whether this fact is applicable to dengue endemic regions as well as assess the impact of human mobility when developing predictive models for dengue incidence of a particular geographical region.
Recommended citation: Dharmawardana, K. G. S., Lokuge, J. N., Dassanayake, P. S. B., Sirisena, M. L., Fernando, M. L., Perera, A. S., & Lokanathan, S. (2017, December). Predictive model for the dengue incidences in Sri Lanka using mobile network big data. In Industrial and Information Systems (ICIIS), 2017 IEEE International Conference on (pp. 1-6). IEEE http://lasanthafdo.github.io/files/iciis-dengue-predictive-models.pdf
Predicting population-level socio-economic characteristics using Call Detail Records (CDRs) in Sri Lanka
Published in Houston, TX, USA, 2018
Prior work has shown that mobile network big data can be used as a high-frequency alternative data source to derive proxy measures that have strong predictive capacity to estimate census and poverty data in developing countries. Given that the observations from these studies can be dependent on local context and regional characteristics, we replicate this work targeting two regions in Sri Lanka
Recommended citation: Fernando, L., Surendra, A., Lokanathan, S., & Gomez, T. (2018, June). Predicting population-level socio-economic characteristics using Call Detail Records (CDRs) in Sri Lanka. In Proceedings of the Fourth International Workshop on Data Science for Macro-Modeling with Financial and Economic Datasets (p. 1). ACM. http://lasanthafdo.github.io/files/dsmm-socio-economic.pdf
research
Spatio-temporal forecasting of dengue outbreaks
Published:
In this project, we use mobile network big data to model human movement patterns. Then using these human mobility models, we make use of other related data sources as well to develop machine learning models to predict dengue outbreaks for a spatial administrative district of Sri Lanka, 2 weeks ahead of time.
Predicting population level socio-economic characteristics using call detail records (CDRs)
Published:
Usage patterns in calling behaviour as well as movement patterns have been shown to correlate with socio-economic levels. In this project, we use Call Detail Records (CDRs) to derive proxy indicators on mobility, consumption and social behaviours of mobile phone subscribers at a large scale to investigate which indicators correlate most in a Sri Lankan regional context.
Privacy-preserving CDRs from mobile phone subscriber profiles
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Generated fictional privacy-preserving CDRs that maintain population-level behavioral characteristics of the original data set for sharing purposes.
Predicting migration from the ego network of a mobile phone subscriber
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In this project, we developed novel measures of social and spatial entropy using large-scale pseudonymized CDRs in Sri Lanka by extending prior work. Currently exploring the results to derive possible migration and mobility behaviour related insights of an ego user.
teaching
Supervisor - Final Year Undergraduate Projects
Project Supervision, University of Moratuwa, Department of Computer Science & Engineering, 2016
Supervised multiple ftinal year undergradute group projects related to large scaled data processing frameworks and epidemic modeling.
Teaching Assistant - Undergradute Courses
Undergraduate courses, University of Moratuwa, Department of Computer Science & Engineering, 2016
Teaching assistant for multiple undergraduate computer science courses.
Visiting Lecturer - Undergraduate Courses
Undergraduate courses, University of Moratuwa, Department of Computer Science & Engineering, 1900
Conducted visiting lectures for the final year undergradute courses on Machine Learning in 2017 and 2018. I also conducted visiting lectures for the Distributed Systems course in 2019.
Guest Lecturer - Graduate Courses
Graduate courses, University of Moratuwa, Department of Computer Science & Engineering, 2017
Conducted guest lectures for master’s level gradute course on Big Data Analytics Technologies.