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Healthcare experts have recently turned towards the use of Biosimulation models to understand the multiple or different causative factors that cause impairment in human organs. The applications of biosimulations have been applied in different biological systems ranging from human ear, cardiovascular, to neurovascular research using Finite Element Method (FEM). FEM provide a mathematical framework...
Collaborative filtering (CF) based rating prediction systems predict unknown ratings of a user for an item, based on the analysis made on how similar users rate similar items. Model based approaches such as cluster models provide efficient means to find out similar users or similar items as they inherently reduce the search space by previously grouping similar users or items into clusters. Hence,...
Statistical language models are central to many applications that use semantics. Recurrent Neural Networks (RNN) are known to produce state of the art results for language modelling, outperforming their traditional n-gram counterparts in many cases. To generate a probability distribution across a vocabulary, these models require a softmax output layer that linearly increases in size with the size...
Biosimulation models are used to understand the multiple or different causative factors that cause impairment in human organs. Finite Element Method (FEM) provide a mathematical framework to simulate dynamic biological systems, with applications ranging from human ear, cardiovascular, to neurovascular research. Finite Element (FE) Biosimulation experiments produce huge amounts of numerical data. Visualizing...
Attribute Based Access Control (ABAC) models are designed with the intention to overcome the shortcomings of classical access control models (DAC, MAC and RBAC) and unifying their advantages. In ABAC, the access control is provided based on generic attributes of entities. Many organizational security policies condition access decisions on attributes. OWL can be used to formally define and process...
In this work, we propose a temporal aggregation scheme for sentiments expressed in social networks. The proposed method discounts for the bias caused in aggregation due to classification errors while providing confidence intervals. A computationally efficient prediction and interpolation scheme of temporal progression is discussed that accounts for the heteroscedastic nature of noise. To this end,...
Mobile web browsing has inherent usability and content discovery problems that warrants alternate browsing paradigms. To provision improved web usability, a server hosted multi-topic content indexing system and a client-based topic cluster solution has been developed that allows the user to browse the web based on content semantics alone. Semantic connections between content are established based...
Commonsense knowledge is considered the basis for machine understanding of natural language semantics. In this paper, we propose a new method for fine-grained commonsense knowledge extraction using dependency graphs built through an unsupervised method. We implement the method on a large-scale text collection, and show how our knowledge model can be applied to develop a generic pronoun resolution...
This paper presents a computational model that considers the relationship between operational and physical conditions of the spraying process in agriculture machinery. The model has as outputs the droplets mean diameter and the spray angle produced by full cone nozzles, which are calculated using physicalconditionssuchasnozzlegeometricparameters, physical characteristics of the liquid to be sprayed...
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