ITRU - 2013ITRU Research Symposiumhttp://dl.lib.uom.lk/handle/123/147252024-03-29T06:08:28Z2024-03-29T06:08:28ZVoice Disorder Recognizer to Aid Diagnosis of a Speech PathologistHettiarachchi, YKWithanage, DKhttp://dl.lib.uom.lk/handle/123/126682019-08-08T09:48:55ZVoice Disorder Recognizer to Aid Diagnosis of a Speech Pathologist
Hettiarachchi, YK; Withanage, DK
In the field of medicine, currently a variety
of methods are used to identify the pathologies in the
human speech production system. The most common
drawbacks of those methods are the discomfort for the
patient caused during inspection, the dependency of
the results on medical practitioner’s experience and
the high cost of diagnosis involved if advanced systems
are used. This research discusses how to overcome
those drawbacks by using an ICT tool that can provide
quantitative evidence of the vocal disorder of patients
to medical practitioners to diagnose pathologies in
deceased speech producing system of patients.
Skin Wound Analysis SystemRanasinghe, CDIgalawithana, TCUdayanga, SMRHettiarachchi, SYChaminda, HThttp://dl.lib.uom.lk/handle/123/126102019-08-08T09:47:55ZSkin Wound Analysis System
Ranasinghe, CD; Igalawithana, TC; Udayanga, SMR; Hettiarachchi, SY; Chaminda, HT
In modern medical science, there is a growing trend
of applying Information Technology into manual routines.
Automated skin wound analysis is a novel approach in
treatment of skin wounds. The system is intended to analyze
different types of skin wounds/lesions by using digital image
processing techniques. Diabetic ulcers, skin-grafted burn
wounds and nail lesions have been chosen for analysis. Nail
lesions require an identification process whereas diabetic
ulcers and skin-grafted burn wounds require an analysis of
the healing process. A semantic web search is performed in
order to verify the identification of nail lesions. The system
also generates line graphs in order to facilitate the assessment
of the healing process. A 3D model of the diabetic ulcer is
created based on the data captured by an IR sensor-based
mechanism. This wound analysis system is expected to help
the doctor’s diagnosis process immensely. The system
provides quantitative and accurate results on wound healing.
Moreover, it supports better comparisons and decision
making.
Sentiment Analysis for Social MediaJayasanka, RASCMadhushani, MDTMarcus, ERAberathne, IAAUPremaratne, SChttp://dl.lib.uom.lk/handle/123/126092019-08-08T09:47:04ZSentiment Analysis for Social Media
Jayasanka, RASC; Madhushani, MDT; Marcus, ER; Aberathne, IAAU; Premaratne, SC
Sentiment analysis, the automated extraction of
expressions of positive or negative attitudes from text has
received considerable attention from researchers during the past
decade. In addition, the popularity of internet users has been
growing fast parallel to emerging technologies; that actively use
online review sites, social networks and personal blogs to express
their opinions. They harbor positive and negative attitudes about
people, organizations, places, events, and ideas. The tools
provided by natural language processing and machine learning
along with other approaches to work with large volumes of text,
makes it possible to begin extracting sentiments from social
media. In this paper we discuss some of the challenges in
sentiment extraction, some of the approaches that have been
taken to address these challenges and our approach that
analyses sentiments from Twitter social media which gives the
output beyond just the polarity but use those polarities in
product profiling, trend analysis and forecasting. Promising
results has shown that the approach can be further developed to
cater business environment needs through sentiment analysis in
social media.
Recognition of online learner emotions through facial expressions: online learner facilitatorChethana, BASRukmal, KWJRathnayake, HCRandeni, RPKJSandanayake, TChttp://dl.lib.uom.lk/handle/123/125782019-08-08T09:46:17ZRecognition of online learner emotions through facial expressions: online learner facilitator
Chethana, BAS; Rukmal, KWJ; Rathnayake, HC; Randeni, RPKJ; Sandanayake, TC
Emotions play an essential role in decision making,
managing, perceiving, learning and influencing the thinking
process of humans. Emotions are also important in teaching
and learning and often find expression in particular ways,
such as interactions with others, as well as interest and
motivation in learning. However the influence of emotions on
learning is still under-emphasized. Continuous and increasing
exploration of the complex set of parameters surrounding
online learning reveals the importance of the emotional states
of learners and especially the relationship between learning
and affective behavior. Automated learner facilitator is a
system that has ability to capture the learners’ facial
expression and comprehend that data. The system always
detects a user’s facial expressions and recognized the changes
in those facial expressions. The proposed actions were based
on an experiment carried out among in the Sri Lankan
university system regarding online learner behaviour during
learning. The system focuses on investigate the current
approaches in facial expression recognition and application
them into the field of online learning to solve the problems
related to learner facilitation. The results of the experiment
have been used for new developments in e-learning courses
and thereby the performance of e-learners is expected to be
enhanced.