Sampath Deegalla

Sampath Deegalla
University of Peradeniya | UOP · Department of Computer Engineering

Ph.Lic. B.Sc. Eng.

About

30
Publications
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272
Citations

Publications

Publications (30)
Conference Paper
Full-text available
The appropriate use of Information and Communications Technology (ICT) in teaching and learning has been challenging for many higher educational institutes during the COVID-19 pandemic. The study examined the demographic factors that influence the adoption and integration of ICT to enhance the university teaching and learning process. The study ado...
Article
Full-text available
Dengue fever is a systemic viral infection of epidemic proportions in tropical countries. The incidence of dengue fever is ever increasing and has doubled over the last few decades. Estimated 50million new cases are detected each year and close to 10000 deaths occur each year. Epidemics are unpredictable and unprecedented. When epidemics occur, hea...
Article
The random subspace and the random projection methods are investigated and compared as techniques for forming ensembles of nearest neighbor classifiers in high dimensional feature spaces. The two methods have been empirically evaluated on three types of high-dimensional datasets: microarrays, chemoinformatics, and images. Experimental results on 34...
Preprint
div>Abstract: Stock forecasting is challenging because of stock volatility and dependability on external factors, such as economic, social, and political factors. This motivates investors to seek tools to identify stock trends to reap profits. In this research, we compared several heterogeneous ensembles for financial forecasting, including averag...
Preprint
div>Abstract: Stock forecasting is challenging because of stock volatility and dependability on external factors, such as economic, social, and political factors. This motivates investors to seek tools to identify stock trends to reap profits. In this research, we compared several heterogeneous ensembles for financial forecasting, including averag...
Thesis
Full-text available
Emerging of the infectious diseases such as Dengue, have become a major challenge for the world. Use of indicatorbased surveillance systems is the traditional approach of monitoring diseases, which uses structured data. Use of event-based surveillance systems is the modern approach, where unstructured data such as information from the internet and...
Research
Full-text available
Since the usage of mobile devices and computers has increased, Internet-based resources have become a medium in which people can share and get to know health information directly and quickly. Internet-based resources such as newspaper articles, social media feeds are providing valuable information about public health surveillance. By analyzing and...
Conference Paper
Full-text available
This research is intended to identify the association between the Learning Style (LS) and the learners’ access biasness over e-learning activities using Data Mining (DM). Such associations can be used for proposing guidelines to develop learner based dynamic online learning environments.
Conference Paper
Fast Internet connectivity and billions of websites have made World Wide Web an attractive place for people to use the Internet in their day-to-day life. Educational institutes provide the Internet access to students mainly for educational purposes. However, most of the time, students are allowed to access any content on the web. Therefore, the ful...
Article
Full-text available
The focus of this research was to use Educational Data Mining (EDM) techniques to conduct a quantitative analysis of students interaction with an e-learning system through instructor-led non-graded and graded courses. This exercise is useful for establishing a guideline for a series of online short courses for them. A group of 412 students' access...
Article
Full-text available
Plagiarism is one of the growing issues in academia and is always a concern in Universities and other academic institutions. The situation is becoming even worse with the availability of ample resources on the web. This paper focuses on creating an effective and fast tool for plagiarism detection for text based electronic assignments. Our plagiaris...
Conference Paper
Full-text available
User interfaces in mobile applications are complex since they need to provide sufficient features to variety of users in a restricted space where a small number of components are available. When user acquires expertise in the system they expect user interfaces which satisfy their unique needs. Therefore, user interfaces in mobile applications shoul...
Conference Paper
Full-text available
Image retrieval in general and content based image retrieval in particular are well-known research fields in information management. A large number of methods have been proposed and investigated in both areas but satisfactory general solution have still not been developed. An image contains several types of visual information which are difficult to...
Conference Paper
Often high dimensional data cause problems for currently used learning algorithms in terms of efficiency and effectiveness. One solution for this problem is to apply dimensionality reduction by which the original feature set could be reduced to a small number of features while gaining improved accuracy and/or efficiency of the learning algorithm. W...
Conference Paper
Full-text available
Using computers to answer natural language questions is an interesting and challenging problem. Generally such problems are handled under two categories: open domain problems and close domain problems. This paper presents a system that attempts to solve close domain problems. Typically, in a close domain, answers to questions are not available in t...
Thesis
The predictive performance of the simple k nearest neighbor (kNN) classi�cation is often poor for high-dimensional datasets such as images and microarrays. In this thesis, we investigate how to improve performance of nearest neighbor classi�cation in high dimensions using dimensionality reduction. In particular, we investigate how to fuse the resul...
Conference Paper
Full-text available
In previous studies, performance improvement of nearest neighbor classification of high dimensional data, such as microarrays, has been investigated using dimensionality reduction. It has been demonstrated that the fusion of dimensionality reduction methods, either by fusing classifiers obtained from each set of reduced features, or by fusing all r...
Conference Paper
Full-text available
Dimensionality reduction has been demonstrated to improve the performance of the k-nearest neighbor (kNN) classifier for high-dimensional data sets, such as microarrays. However, the effectiveness of different dimensionality reduction methods varies, and it has been shown that no single method constantly outperforms the others. In contrast to using...
Conference Paper
Full-text available
Dimensionality reduction can often improve the performance of the k-nearest neighbor classifier (kNN) for high-dimensional data sets, such as microarrays. The effect of the choice of dimensionality reduction method on the predictive performance of kNN for classifying microarray data is an open issue, and four common dimensionality reduction methods...
Conference Paper
Full-text available
The computational cost of using nearest neighbor classification often prevents the method from being applied in practice when dealing with high-dimensional data, such as images and micro arrays. One possible solution to this problem is to reduce the dimensionality of the data, ideally without loosing predictive performance. Two different dimensiona...

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