Research Publications Authored by SLIIT Staff
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This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.
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Publication Embargo Automated Child Social Attention Evaluation(IEEE, 2022-12-09) Sandunika Wasala, K; Dhanawansa, V; Velayuthan, M; Samarasinghe, PProviding proper care for children with attention difficulty disorder is crucial, one way to ensure this is early identification of these disorders. In Sri Lanka, a developing country, it is difficult to find resources such as clinics, clinical expertise, and other resources which are essential for diagnosis. The absence of these apparatuses risks the mental well-being of the child as well as access to help. Hence a need arises to develop an automated social attention evaluation system. This will serve as the first line of diagnosis and help the parents/guardians secure the help required from an early age for the child. To the best of the authors’ knowledge, no solution of this nature is readily available for the Sri Lankan community so far. Keeping the low-income bracket of the country in mind, we propose a solution that can be easily deployed even on a cheap mobile/tablet-like device. It is difficult to perform these evaluations for children in similar settings as adults, as they are easily distracted. Therefore, care must be taken to grab the child’s attention throughout the evaluation process. In this research, we developed applications for children at different levels and each level assesses child attention between social objects and non-social objects through a child-friendly game, as they have sufficient visual stimuli to hold the child’s attention. In this study we investigated the screen time spent by the child, the attention of the child on different categories of images (High Autism Interested or Low Autism Interested images), and the switching patterns of the attention between these images. Only typical children were evaluated for this research due to the pandemic situation as well as other internal problems in the country. This system will test and evaluate atypical children in our future work.Publication Embargo Speech Master: Natural Language Processing and Deep Learning Approach for Automated Speech Evaluation(IEEE, 2021-12-06) Kooragama, K.G.C.M; Jayashanka, L. R. W. D; Munasinghe, J. A; Jayawardana, K. W; Tissera, M; Jayasingha, T. BEvery English speaker wishes to expertise his/her public speaking skills sharply. However, it is extremely difficult and requires a significant amount of practice and experience on an individual basis. This paper introduces a novel online tool “Speech Master” to practice and improve public English speech delivering skills in a professional manner. Using natural language processing, machine learning, and deep learning approaches, the proposed system analyzes the user's speech in terms of content, grammatical accuracy, grammatical richness, facial expressions, and flow. The accuracy was checked by comparing actual results taken from experts with the predicted results obtained from the tool. “Speech Master” achieves an average accuracy of more than 80% and produces a better overall result. This novel tool benefits English speakers all over the world by meeting the demand for a simple and easy-to-use solution for improving or practicing English speech delivery skills; enhancing oratory skills, boosting confidence, and delivering well-articulated speeches.Publication Open Access Evaluation of Satellite Rainfall Products over the Mahaweli River Basin in Sri Lanka(Hindawi, 2022-04) Perera, H; Fernando, S; Gunathilake, M. B; Sirisena, J; Rathnayake, Ue availability of accurate spatiotemporal rainfall data is of utmost importance for reliable predictions from hydroclimatological studies. Challenges and limitations faced due to the absence of dense rain gauge (RG) networks are seen especially in the developing countries. erefore, alternative rainfall measurements such as satellite rainfall products (SRPs) are used when RG networks are scarce or completely do not exist. Noteworthy, rainfall data retrieved from satellites also possess several uncertainties. Hence, these SRPs should essentially be validated beforehand. e Mahaweli River Basin (MRB), the largest river basin in Sri Lanka, is the heart of the country’s water resources contributing to a signi cant share of the hydropower production and agricultural sector. Given the importance of the MRB, this study explored the suitability of SRPs as an alternative for RG data for the basin. Daily rainfall data of six types of SRPs were extracted at 14 locations within the MRB. ereafter, statistical analysis was carried out using continuous and categorical evaluation indices to evaluate the accuracy of SRPs. Nonparametric tests, including the Mann-Kendall and Sen’s slope estimator tests, were used to detect the possibility of trends and the magnitude, respectively. Integrated MultisatellitE Retrievals for Global Precipitation Measurement (IMERG) outperformed among all SRPs, while Precipitation Estimation from Remotely Sensed Information using Arti cial Neural Networks (PERSIANN) products showed dire performances. However, IMERG also demonstrated underestimations when compared to RG data. Trend analysis results showcased that the IMERG product agreed more with RG data on monthly and annual time scales while Tropical Rainfall Measurement Mission Multisatellite Precipitation Analysis–3B42 (TRMM-3B42) agreed more on the seasonal scale. Overall, IMERG turned out to be the best alternative among the SRPs analyzed for MRB. However, it was clear that these products possess signi cant errors which cannot be ignored when using them in hydrological applications. e results of the study will be valuable for many parties including river basin authorities, agriculturists, meteorologists, hydrologists, and many other stakeholders.Publication Embargo Self-speech evaluation with speech recognition and gesture analysis(IEEE, 2018-10-02) Shangavi, S; Jeyamaalmarukan, S; Jathevan, A; Umatharsini, M; Samarasinghe, PSpeaking helps people to improve their communication, public speaking and leadership skills. There are two main techniques that help a speaker to deliver a meaningful speech. The techniques are voice transition which expresses a verbal message and gestures that convey the message to an audience. A famous organization to help and improvise speech is Toastmasters. Their systems of evaluation are such as, Tracking Filler words, Usage of Redundant words and Phrases, Checking Grammar and Pronunciation, Usage of Body Movements and Gestures, Tracking Vocal Variations and Time Management. If an ordinary person wants to self-evaluate his or her speech, that person has to be a member of a Toastmasters Club or any other speech improvising organization. By using our application, it is possible for a person to evaluate his or her own speech without depending on an organization. All the above-mentioned criteria in manual evaluation processes are included in this application. Since nowadays mobile applications are frequent in use, our system is proposed in Android Platform. Several techniques and methods are used to interconnect with Android such as OpenCV, Microsoft Cognitive Services and MATLAB in order to achieve the objectives of the application. Acoustic Model, Support Vector Model (SVM), Hidden Markov Model (HMM) are some models used to build the application more efficient by giving approximately accurate results.Publication Open Access An evaluation of genetic diversity in micropropagated anthurium using starch gel electrophoresis(Postgraduate Institute of Agriculture, University of Peradeniya: Peradeniya, 1992) Peiris, S; Mantell, S. H; Peiris, C. N; Senanayake, Y. D. AAnthurium andreanum Lind is a cut flower which is in high demand in the local and export cut flower trades in Sri Lanka. For commercial production of export anthurium cut flowers, it is essential that the selected elite qualities of the flowers borne on this original mother stock plants are maintained consistantly through many generations on vegetative multiplication. Tliis paper reports on stanch gel electrophoresis which was adapted successfully on anthuriums to evaluate genetic diversity if any, in plants derived either from seedlings, conventional stem cuttings or micropropagated clonal plants. Buffered leaf extracts were compared by means of horizontal starch gel electrophoresis to check the variability in cv. 'Crinkled Red'. Isoenzyme banding patterns of malic dehydrogenase (MDH), 6 phosphogluconic dehydrogenase (6 PGDH), phosphogluco isomerase (PGI) and diaphorase (DIAP) were used. Extracts of 105 seedlings, 60 clonal plants produced through rhizome cuttings and 150 in vitro propagated plants were compared to detect possible somaclonal variations in the daughter plants produced. Results of starch gel electrophoresis showed that extracts of seedling plants contained variations, expressed as percentages showing deviant patterns in all five isoenzyme systems assessed: MDH 14%, 6 PGDH 13%, GOT 12%, PGI 14% and DIAP 16%. None of the clonal plants or in vitro propagated plants tested using this technique showed variations in any of the isoenzyme compared. Tlie results of this study showed the genetic diversity in anthwium seedling plants and confirmed that stability was maintained in vegetatively propagated and in vitro propagated plants. Since in vitro propagation produces a large number of uniform and genetically stable plants, in vitro multiplication would appear to be suitable for use in the Sri Lankan floriculture industryPublication Open Access Evaluation of future climate and potential impact on streamflow in the Upper Nan River basin of Northern Thailand(Hindawi, 2020-10) Rathnayake, U. S; Gunathilake, M. B; Amaratunga, V; Perera, AWater resources in Northern Thailand have been less explored with regard to the impact on hydrology that the future climate would have. For this study, three regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment (CORDEX) of Coupled Model Intercomparison Project 5 (CMIP5) were used to project future climate of the upper Nan River basin. Future climate data of ACCESS_CCAM, MPI_ESM_CCAM, and CNRM_CCAM under Representation Concentration Pathways RCP4.5 and RCP8.5 were bias-corrected by the linear scaling method and subsequently drove the Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS) to simulate future streamflow. This study compared baseline (1988–2005) climate and streamflow values with future time scales during 2020–2039 (2030s), 2040–2069 (2050s), and 2070–2099 (2080s). The upper Nan River basin will become warmer in future with highest increases in the maximum temperature of 3.8°C/year for MPI_ESM and minimum temperature of 3.6°C/year for ACCESS_CCAM under RCP8.5 during 2080s. The magnitude of changes and directions in mean monthly precipitation varies, with the highest increase of 109 mm for ACESSS_CCAM under RCP 4.5 in September and highest decrease of 77 mm in July for CNRM, during 2080s. Average of RCM combinations shows that decreases will be in ranges of −5.5 to −48.9% for annual flows, −31 to −47% for rainy season flows, and −47 to −67% for winter season flows. Increases in summer seasonal flows will be between 14 and 58%. Projection of future temperature levels indicates that higher increases will be during the latter part of the 20th century, and in general, the increases in the minimum temperature will be higher than those in the maximum temperature. The results of this study will be useful for river basin planners and government agencies to develop sustainable water management strategies and adaptation options to offset negative impacts of future changes in climate. In addition, the results will also be valuable for agriculturists and hydropower planners.