Research Papers - Department of Electrical and Electronic Engineering
Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/679
Browse
148 results
Filters
Advanced Search
Filter by
Settings
Search Results
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, U; Manatunga, D.CThe 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.Publication Open Access YOLO-MOTF: Motion-temporal fusion for dynamic object detection with a moving camera for assistive wheelchairs(Elsevier B.V., 2026-03-09) Tennekoon, S; Wedasingha, N; Welhenge, A; Abhayasinghe, N; Murray, IDynamic object detection is fundamental to advancing vision-based navigation systems, particularly in environments where the camera itself is in motion. Despite progress in detection algorithms, existing approaches often struggle with challenges such as egomotion, short-term occlusions, temporal discontinuities, and computational cost. This paper presents YOLO-MOTF, a novel knowledge-based model that integrates spatial features with motion cues, especially for operation under moving camera conditions. The framework incorporates a hybrid motion compensation strategy to suppress camera-induced distortions and an occlusion handling buffer to preserve object trajectories through discontinuities. Additionally, a motion attention gating mechanism selectively reinforces moving object predictions by intersecting fused motion masks with semantic outputs. The proposed system achieves an F1 score of 88.6% and a 93% reduction in flow processing compared to dense flow methods, underscoring its robustness and efficiency in dynamic environments. Beyond theoretical contributions, the model demonstrates direct applicability in real-world knowledge-based decision systems, including healthcare applications such as assistive wheelchair navigation, as well as assistive robotics, autonomous navigation, and surveillance.Publication Open Access Bi-directional long short-term memory based ensemble deep learning framework for non-linear steam turbine power forecasting: a biomass fuelled case study(Elsevier Ltd, 2026-04-10) Perera, H; Jayasekara, S; Wijesinghe, R.E; Silva, B. N; Cha, HIn palm oil manufacturing, steam turbines powered by biomass fuel are central to energy generation. However, fluctuating load demands and temporal variations lead to inefficiencies, while limited and variable supply of biomass waste constrains boiler feed flexibility. Current index-based boiler feeding methods overlook actual load demands and waste availability, resulting in significant energy wastage. This study presents a novel ensemble deep learning model combining Bidirectional Long Short-Term Memory (Bi-LSTM) and Gated Recurrent Units (GRU) with Attention Layers, trained on an eight-year operational dataset with structured preprocessing and feature selection, to forecast steam turbine power generation. The model captures complex non-linear temporal patterns more effectively than conventional and standalone ML models, achieving a Root Mean Square Error (RMSE) of 0.0684, Mean Absolute Error (MAE) of 0.0414, and an R-squared (R2) value of 0.9832, which outperformed eight benchmark models by approximately 25% in prediction accuracy. Additionally, the framework incorporates operational parameters such as kVA, total energy, and Fresh Fruit Bunch (FFB) production to dynamically optimise biomass feed rates, balancing energy output with resource availability. This approach minimises energy wastage, reduces grid reliance, and promotes both sustainability and profitability.Publication Embargo Fly-Energy Ecosystem: A Game-Theoretic Hybrid SWIPT Framework for UAV-Assisted Rural Wireless Systems(Institute of Electrical and Electronics Engineers Inc., 2026) Sooriarachchi, V.P; Jayakody, D. N.K; Muthuchidambaranathan P.The increasing use of IoT and related solutions in rural environments brings the growing need for energy-efficient and energy-aware solutions. This paper proposes a novel Stack-elberg game-theory-assisted hybrid wireless energy harvesting approach for unmanned aerial vehicle (UAV), which incorporates SimultaneousWireless Information and Power Transfer (SWIPT) systems designed specifically for remote and rural environments with conventional wireless power transfer (WPT). A multi-UAVs, multi-user scenario is considered where UAVs collect information from ground-level users while simultaneously providing WPT to the users. The proposed framework enables sustainable operation of remote monitoring systems in rural areas where conventional power infrastructure is limited or unavailable, contributing to more resilient and energy-efficient IoT deployments in challenging environments. The simulation results show that the proposed method achieves scalable performance and significant improvements in SINR and energy harvesting efficiency.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.Publication Embargo Receiver-Centric Waveform Design: A New Frontier in SWIPT(Institute of Electrical and Electronics Engineers Inc., 2026-01-15) Vithanage, G. S; Jayakody, D. N.K; Krikidis, IIn this work a receiver-centric waveform design technique for simultaneous wireless information and power transfer (SWIPT) is proposed, eliminating the traditional trade-off between energy harvesting (EH) efficiency and information transfer (IT) integrity. By injecting pulses into the receiver, the peak-to-average power ratio (PAPR) of the received signal is increased, using diode nonlinearity to enhance EH without affecting IT. Particle swarm optimization (PSO) is used to tune the pulse parameters to obtain the maximum harvest power under practical constraints. The Monte Carlo simulation results demonstrate superior EH performance compared to existing waveform optimization schemes. The method remains robust under common IT optimizations, such as selective mapping (SLM) and partial transmit sequence (PTS), confirming its compatibility and scalability for real-world SWIPT systems.Publication Open Access Advancing Object Detection: A Narrative Review of Evolving Techniques and Their Navigation Applications(Institute of Electrical and Electronics Engineers Inc., 2025-03-17) Tennekoon, S; Wedasingha, N; Welhenge, A; Abhayasinghe, N; Murray Am, IObject detection plays a pivotal role in advancing computer vision systems by enabling machines to perceive and interact intelligently with their environments. Despite significant advancements, comprehensive exploration of its evolution and applications in navigation remains underrepresented. This review paper examines the evolution of object detection technologies, from early methodologies to contemporary advancements, and their critical role in navigation tasks. The emphasis was on the significance of contextual learning in enhancing object detection performance by leveraging spatial and temporal information. Furthermore, the limitations of conventional approaches that rely heavily on hand-engineered features are examined. It is then demonstrated that contextual learning facilitates automated feature extraction, resulting in improved accuracy exceeding a 50% increase and adaptability in diverse applications. The review concludes by outlining future trends and opportunities for further advancements in object detection and, underscoring its transformative impact on autonomous navigation and beyond. In summary, this review contributes to a comprehensive understanding of object detection technologies by offering insights into their evolution, highlighting their applications in navigation, and providing guidance for future research in context-aware systems.Publication Open Access Three-Dimensional Assessment of Dental Enamel Microcrack Progression After Orthodontic Bracket Debonding Using Optical Coherence Tomography(Multidisciplinary Digital Publishing Institute (MDPI), 2025-01) Saleah, S.A; Hamdan, A.H; Seong, D; Ravichandran, N. K; Wijesinghe, R.E; Han, S; Kim, J; Jeon, M; Park, H. SThe current study aimed to quantify the length progression of enamel microcracks (EMCs) after debonding metal and ceramic brackets, implementing OCT as a diagnostic tool. The secondary objectives included a three-dimensional assessment of EMC width and depth and the formation of new EMCs. OCT imaging was performed on 16 extracted human premolars before bonding and after debonding. Debonding was conducted with a universal Instron machine, with ARI values recorded. Additionally, 2D and 3D OCT images were employed to detect EMC formation and progression. Enface images quantified the length, width, and number of EMCs, and the length and width were analyzed using Image J (1.54f) and MATLAB (R2014b), respectively. Sagittal cross-sectional images were used for EMC depth analysis. A paired t-test showed significant differences in the length, width, and number of EMCs after debonding (p-value < 0.05), while the Wilcoxon non-parametric test indicated significant EMC depth changes (p-value < 0.05). No significant results were identified for the EMC number in ceramic brackets and EMC depth in metal brackets. Three-dimensional OCT imaging monitored existing EMCs at higher risk of progression and detected new EMCs following orthodontic bracket debonding. This study provides novel insights into EMC progression regarding the length, width, depth, and number after debonding.Publication Open Access Next-Gen Decoding: Non-Binary LDPC Algorithms for Emerging Power Line and Visible Light Communications(Institute of Electrical and Electronics Engineers Inc, 2025-06-09) Ullah, W; Yang, F; Choi, K; Jayakody, D.N.KNon-Binary Low-Density Parity-Check (LDPC) codes have gained significant attention due to their remarkable error correction capabilities in various communication systems. Decoding algorithms play a pivotal role in realizing the potential of non-binary LDPC codes. This paper provides a comprehensive review and analysis of non-binary LDPC decoding algorithms, focusing on their efficiency, complexity, and performance. Furthermore, recent advancements and innovations in non-binary LDPC decoding algorithms are discussed, such as improved message passing strategies, layered decoding techniques, and adaptive algorithms. The review also highlights challenges and open research directions in non-binary LDPC decoding, such as mitigating error floors, reducing decoding complexity, and integrating with emerging communication technologies. Finally, the paper draws conclusions on the current state of non-binary LDPC decoding algorithms, underscoring their promising applications in wireless communication, visible light communication (VLC), and power line communication (PLC). Simulation results demonstrate a marked improvement in bit error rate performance for both VLC and PLC systems, highlighting the practical potential of these advanced decoding techniques.Publication Open Access Multi-User Sparse Vector Coding for eXtreme Ultra-Reliable Low-Latency Communication in Beyond 5G(Institute of Electrical and Electronics Engineers Inc., 2025-03-14) Sabapathy, S; Maruthu, S; Jayakody, D. N.KShort A short packet transmission scheme, such as Sparse Vector Coding (SVC), is a primary candidate for achieving ultra-low latency and high-reliability communication (URLLC). This paper proposes a spectral-efficient multi-user SVC (MU-SVC) scheme for achieving next-generation URLLC or eXtreme URLLC (xURLLC) in beyond 5G (B5G) communications. The key idea is to transmit multiple user information within a single sparse vector where the users are segregated into far users (FU) and near users (NU) depending on the distance from the base station. The classification into FU and NU paves way to optimize resource allocation, user fairness, manage interference, ensure reliable communication and quality of service requirements. Firstly, the FU binary data is converted into a sparse vector and secondly, the NU data is modulated and embedded into the non-zero positions of the sparse vector to form an MU-SVC. On transmission, the FU data is obtained through sparse demapping, while the NU adopts symbol detection techniques like the maximum likelihood detector. A new performance metric, called position error rate (PoER), is introduced to study the performance of the FU since it is based on the correct identification of the non-zero positions. Theoretical analyses of PoER and symbol error rate (SER) were carried out for FU and NU, respectively and the results are also validated through Monte-Carlo simulations. Further, the bit error rate, complexity, spectral and latency analyses are performed for MU-SVC and compared with the SVC and enhanced SVC schemes. The simulation results demonstrate an improved spectral efficiency and low latency with high reliability for the proposed MU-SVC scheme, thus, achieving xURLLC with reduced complexity in the multi-user scenario for B5G.