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Issue Date	Title	Author(s)
2016-09-13	Opportunistic Persistent Data Storage	Weerasooriya, W.A.A.C.P.
2016-09-13	Experience-based Personalized Diversification of Recommendations	Vihanga, W.G.Dulakshi
2016-09-13	Bimanual UI Metaphor: Towards Rehabilitation of Limited Fine Motor Skills of Di erently Abled Children N	Abeywickrama, N.D.
2016-09-13	With the widespread adoption of Internet of Things (IoT), it is estimated to become the largest device market in the world more than double the size of smart phones, PC, tablet markets combined. More and more organizations, consumers, businesses and governments are recognizing the bene ts of a connected environment of devices. This also introduce a fundamental dilemma. The data amassed from these devices will equate to an unprecedented volume. This problem propagates when data intelligence is needed, that require the collected data to be transported to a computation source, usually through a network connected to the internet. As current and forthcoming network infrastructure falls short handling this high velocity of data, the need for a robust computation model that processes data at the generated source becomes apparent. We aim to ful ll this void by proposing a novel architecture that is designed based on the Fog computation model. By leveraging the capabilities like reduced latency and data tra c inherent to the Fog computing platform, our architecture thrive to provide enhanced performance to applications that have demanding real time computation needs. Complex event processing is at the core of our computation model, simulating the environment changes captured through sensors in the form of events. Uniqueness of our architecture lies in its Fog to Cloud gateway design, which enable the computation model to take advantage of Cloud computing's resource pools. To resolve the scheduling of events to the Cloud or to the Fog node, we used a novel approach where a rule engine determines the computation source according to the resources of Fog node. To aid the rule engine, we formulated an event dependency resolving mechanism based on event trees. Also an extension of our rule engine concept is presented that predicts the resource values of the Fog node, which can be used schedule events anticipating a future system state. We explore a thorough evaluation and validation process that gauge the e ectiveness, performance and the accuracy of our novel architecture's implementation and its components. System comparison was done with a traditional complex event processing engine that has Cloud as the computation source. In our comprehensive evaluation process, results obtained con rm the implemented systems superior e ectiveness and performance in real time applications. Our study validates the need of the proposed hybrid computation model that makes use of both Fog computing and Cloud computing platforms in cases of applications with real time reaction needs.	Madumal, M.B.A. Prashan
2016-09-09	Experience-based Personalized Diversification of Recommendations	Vihanga, W.G.Dulakshi; Urbina, Andrea Barraza-
2016-09-09	An Assistive Technology Framework for Communication with Hearing Impaired Persons	Amarasinghe, M. C. A.
2016-09-09	A Data Delivery Protocol for Extremely Resource Constrained Wireless Sensors	Hapuarachchi, R. E.
2016-09-09	An approach to predict the survival time of Acute Lymphoblastic Leukemia (ALL) patients	Amaraweera, R.J
2016-09-09	INVESTIGATION OF IDENTIFYING COVER SONGS FOR SINHALA SONGS UNDER MUSIC INFORMATION RETRIEVAL	Hemali, K.H.V.
2016-09-09	User-friendly Web Based Mechanism to Incorporate Knowledge Evolution for Ontologies targeting Ontology-Illiterate Domain Users	Samarasinghe, S. W. A. Dilini M.
2016-09-09	Supervised Learning approach for Singer Identification in Sri Lankan Music	Amarasinghe, R. A.
2016-09-09	“EYES FOR THE BLIND” - GENERATING HIGH QUALITY TEXT-TO-SPEECH VOICES FOR SINHALA	JAYAMANNE, YASORA THEWUNI
2016-09-09	Supervised Learning Approach for Classification of Recorded Songs based on Music Structure Similarity	Peiris, T.S.R
2016-09-09	Querying Federated Ontologies:Using Ontology inter-Operations in Agriculture Domain	Bhagyadith, G.D.S.D.
2016-09-09	Development of a Real-Time Six Degree-of-Freedom Computational Model to Simulate Ram-Air Parachute Dynamics	Gunasinghe, H.M.U.S.
2016-09-09	Prediction of Emotion Stimulated by Music	Nanayakkara, C. V.
2016-09-09	Domain Specific Language For Specifying Operations of a Central Counterparty	Nalinda, Chamin
2016-09-09	Scalable Real Time Entity Resolution on Relational Databases	Tennakoon, J.I.B.
2016-09-09	Radio Tomographic Imaging using Extremely Resource Constrained Devices	De Alwis, A.C.S
2016-09-08	Content Based Cross-Domain Recommendation Using Linked Open Data	Munasinghe, P.P.