Research Publications
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Publication Open Access Anthocyanin (ATH)-incorporating polyvinylpyrrolidone-ethyl cellulose-(2-hydroxypropyl)-β-cyclodextrin (PVP–EC–BCD) nanofiber-based pH sensor for ocular pH detection during accidental chemical spills(Royal Society of Chemistry, 2026-02-03) Sandaruwan, B; Liyanage, R; Costha, P; Dassanayake, R.S; Wijesinghe, R.E; Herath H.M.L.P.B; Nalin de S.K.M; de Silva, R.M; Rajapaksha, S.M; Wijenayake, UThe existing ocular pH detection methods encounter numerous limitations, including low accuracy, poor sensitivity across a wide pH range, and patient discomfort, highlighting the need for innovative approaches. A novel biosensor for ocular pH detection has been developed to assess ocular health and chemical injuries in clinical settings. This study uses the pH-sensitive properties of anthocyanins (ATHs), natural pigments extracted from butterfly pea flowers, to develop a novel pH-responsive nanofiber mat. ATHs are integrated into a polymer blend containing polyvinylpyrrolidone (PVP), ethyl cellulose (EC), and (2-hydroxypropyl)-β-cyclodextrin (BCD) to fabricate electrospun nanofibers. The acquired characterization, employing scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and thermogravimetric analysis (TGA), confirmed the successful fabrication of the ATH-infused nanofibers with a mean diameter ranging from 121 to 396 nm. Four formulations were tested: PVP:EC:BCD:ATH (18 ppm), PVP:EC:BCD:ATH (25 ppm), PVP:EC:BCD:ATH (35 ppm), and PVP:EC:BCD:ATH (50 ppm). Among them, the 50 ppm ATH-incorporating nanofiber mat exhibited the best performance in terms of color clarity, response time, and pH sensitivity. The fabricated 50 ppm ATH incorporating nanofiber mat demonstrated a rapid pH response time of less than 5 seconds (s) while exhibiting a color variation from pink to blue to green across the pH range of 1 to 12, providing a rapid and accurate method for visual pH detection. Based on the color performance of the 50 ppm ATH-incorporating system, a standardized color reference chart was developed to serve as a practical and visual guide for estimating pH levels in clinical applications. Zebrafish toxicity assays were conducted further to validate the safety and biocompatibility of the developed sensor, revealing no significant toxic effects across the range of ATH concentrations.Item Embargo Wet-Neuromorphic Computing: A New Paradigm for Biological Artificial Intelligence(Institute of Electrical and Electronics Engineers, 2025-03-31) Perera, J; Balasubramaniam, S; Somathilaka, S; Wen, Q; Li, X; Kasthurirathna, D; Roohi, A; Nelson, M. TAs we delve into a life governed by artificial intelligence (AI), ongoing research continues to discover new forms of intelligence that are efficient and closely mimic an organism’s brain in terms of performance. This article presents a new concept termed wet-neuromorphic computing, in which biological cells or organisms are leveraged to perform computational tasks using their natural molecular functions. We map key neuromorphic properties to natural biological computing observed in bacteria, 3-D organoids, and Caenorhabditis elegans. To expand beyond the inspiration of the brain to create conventional neuromorphic computing, the study presents a case study that demonstrates bacterial AI computing using the gene regulatory neural network derived from Escherichia coli’s gene regulatory network for pattern recognition, validated through wet lab experiments. Finally, challenges and future directions are discussed.Publication Open Access The Effect of TPACK on ESL Learners' Performance: An Investigation of Teacher Competency in Technology Integration in the Colombo District(School of Education, Faculty of Humanities and Sciences, SLIIT, 2025-10-10) Colombage, L.U.; Abeywickrama,K.R.W. K.H.Given the growing use of technology in education, it is essential to comprehend how Technological Pedagogical Content Knowledge (TPACK) contributes to teachers’ successful learning. This study investigates how the TPACK of secondary-level English as a Second Language (ESL) teachers affects the performance of ESL students byanalysing data gathered from secondary-level ESL teachers in seven schools in the Colombo District using a mixed method approach.Publication Open Access Conceptual Design of Short Range - Low Altitude Fixed Wing Unmanned Aerial Vehicle For Landmine Detection(Sri Lanka Institute of Information Technology, 2023-03-25) Daisan, GOver the past five decades, landmines are creating serious problems all over the world. Even though many UAVs are being developed for demining, many of them are not available to the humanitarian activities. Designing a UAV for demining from the air is challenging and there are only a few UAVs employed in landmines search in Sri Lanka. This research designs a fixed-wing UAV with a total mass of 47 kg, with 10 kg dedicated to payload. It can fly with a maximum speed of 30 m/s continuously for 40 minutes. This UAV detect landmines using ground penetrating radar in no wetted areas. Several manual calculations and software such as Microsoft Excel, XFLR 5, X-Foil, CATIA V5, and ANSYS 19 were used to complete the conceptual design.Publication Embargo Performance Comparison of Sea Fish Species Classification using Hybrid and Supervised Machine Learning Algorithms(IEEE, 2022-10-04) Nalmi, R; Rathnayake, N; Mampitiya, L.IIn the domain of autonomous underwater vehicles, the classification of objects underwater is critical. The hazy effect of the medium causes this obstacle, and these effects are directed by the dissolved particles that lead to the reflecting and scattering of light during the formation process of the image. This paper mainly focuses on exploring the best possible image classifier for the underwater images of the different fish species. The classifications were carried out by different hybrid and supervised machine learning algorithms such as Support Vector Machine (SVM), Random Forest (RF), Neural Networks (NN), Logistic Regression (LR), Decision Tree (DT), and Naive Bayes (NB). This study compares the algorithms’ accuracy and time and analyzes crucial features to decide the most optimal algorithm. Furthermore, the results of this paper depict that using dimension reduction methods such as PCA and LDA increases the accuracy of some algorithms. Random Forest was able to outperforms with a higher accuracy of 99.89% with the proposed feature extraction methods.Publication Embargo Intelligent System to Verify the Effectiveness of Proposed Teacher Transfers Incorporating Human Factors(IEEE, 2022-02-23) Karunanayake, V; Wanniarachchi, J. C; Karunanayake, p; Rajapaksha, SA data center architecture can be determined as the basic structure of a cloud computing data center. However, the expected outcome cannot be obtained even though the tools, technologies, and elements are advanced. It is crucial to select the right architecture as architecture used, which directly affects the operational cost and power consumption of the data center. The SDN, Software Defined Networking, is a novel technology of cloud computing. This SDN is used to separate the control panel and forwarding plane as well, as it enables programmable network components. Therefore, the components of the SDN can easily control and managed. This research aimed to select an SDN-based architecture for a data center. Here, there are two parameters of average throughput and average packet delay on the three existing architectures that are tested using simulation. Then the results are compared with each other. In this research, the accuracy correlations among average packet delay and average throughput are investigated. The Obtained results show that Fat-Tree architecture is the best one among VL2 and hybrid architecture consists with flat tree and VL2 technology in terms of their performances.Publication Embargo Investigating the Performance in SDN Based Data Centers Under Different Network Topologies(IEEE, 2022-02-23) Rankothge, W; Hemachandra, K. G. R. P.; Jayasena, K. P. N; Wijesiri, M. P. MA data center architecture can be determined as the basic structure of a cloud computing data center. However, the expected outcome cannot be obtained even though the tools, technologies, and elements are advanced. It is crucial to select the right architecture as architecture used, which directly affects the operational cost and power consumption of the data center. The SDN, Software Defined Networking, is a novel technology of cloud computing. This SDN is used to separate the control panel and forwarding plane as well, as it enables programmable network components. Therefore, the components of the SDN can easily control and managed. This research aimed to select an SDN-based architecture for a data center. Here, there are two parameters of average throughput and average packet delay on the three existing architectures that are tested using simulation. Then the results are compared with each other. In this research, the accuracy correlations among average packet delay and average throughput are investigated. The Obtained results show that Fat-Tree architecture is the best one among VL2 and hybrid architecture consists with flat tree and VL2 technology in terms of their performances.Publication Open Access Novel Sprinter Assistive Smart Agent for Continuous Performance Improvement(IEEE, 2021-04-06) Subhashana, H; Bandara, C; Bandara, I; Devindi, A; Kuruwitaarachchi, N; Dharmasena, TIn the field of Sports, sprinting is the term used for introducing running over a short distance in a limited time. To date, a method to identify whether sprinters are getting enough speed during the accelerated period is not available so far. This paper proposes a smart agent to recognize the technical precision and performance of a sprinter using wireless hardware devices and a software solution. Smart shoe, track sensor, arm motion detection bracelet are the devices used to collect data from a sprinter. After required data collecting is complete the based web application provides feedback to the sprinter to improve sprinting techniques. This modern technology based system reduces human errors and workload of a trainer and would be highly beneficial for the sports community including coaches and sprinters as it could be accessed through mobile phones. The results of the study show the visualization of sprinter data effectively and an analysis on the obtained data regarding the performance.Publication Open Access IMPACT OF OPERATIONAL LEVEL EMPLOYEES’HAPPINESS ON PERFORMANCE OF HOTEL INDUSTRY IN SRI LANKA(Sabaragamuwa University of Sri Lanka, 2019-10-29) Dissanayaka, D. M. K. S; Malluwawadu, D. D; Mendis, W. N. M; Wickramarachchi, W. A. H. M; Rajapakshe, WThe purpose of this study is to identify the impact of operational level employees’ happiness on organizational performance based on the hotel industry in Sri Lanka. Basically, employee behavior is very critical for an organization. While employees are happy about their job it encourages them to get motivated and perform their job well. As a result, organization can gain performance-oriented results towards them. Happiness is measured by five attributes; job inspiration, organizations shared value, relationships, quality of work life and leadership. In addition, this research identified the employee happiness based on gender, age, marital status, education and years of service. Organizational performance is assessed based on the employee attitudes. Survey method used to collect data through a standard questionnaire. One of Sri Lankan largest hotel chain was selected through the convenient sampling and sample of this research was 350 operational level employees which selected through the random sampling. Pearson correlation, multiple regression analysis used to identify the relationship between independent and dependent variables. Statistical software called SPSS used to analyze the data.Publication Embargo An AI based Chatbot to Self-Learn and Self-Assess Performance in Ordinary Level Chemistry(IEEE, 2020-12-10) Mahroof, A; Gamage, V; Rajendran, K; Rajkumar, S; Rajapaksha, S, K; Wijendra, DEducation is one of the fast-growing fields in the global perspective. Advancement of technology can be used in this sector to provide an effective and a valuable education system. In general, the students are more attracted to displays rather than the textbooks. In Sri Lanka, there is an inadequacy of resources and teachers cannot provide one on one attention to the students. Sri Lanka is not equipped with any platform to self-learn or self-evaluate their performance using an application either. Fortunately, “Edubot” acts as a solution for the stated research gap by providing a self-learning and self-evaluating AI based chatbot platform for Ordinary Level students in Chemistry domain. The self-learning component will provide the students a classroom environment by providing interactive tutorials. Explanatory responses would be given by Edubot by capturing doubts raised by the students and the self-evaluating component will provide an exam-based environment in which the Edubot auto generates the question and answers. The research finding shows that each component has an accuracy of more than 70 percent and helps to achieve the main goal of increasing the resources available to the ordinary level students in the Chemistry domain. This would then lead to an increase in the pass rate of the chemistry subject in the G.C.E Ordinary Level exam.