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Publication Open Access Highly Efficient 3D Object Transmission System for HTC Services in 6G Networks(Faculty of Engineering, 2026-03) Svechnikov, D; Volkov, A; Marochkina,A; Muthanna, A; Kouhceryavy, AIn recent years, advancements in technology have brought forth a new frontier in visual communication. Holography is a technique that captures and reproduces three-dimensional (3D) images with an unprecedented level of realism and depth, has emerged as a groundbreaking method for conveying visual information. Unlike traditional images and videos, holography recreates scenes with full parallax, enabling viewers to perceive objects from various angles. The transmission of holographic images presents both exciting possibilities and unique challenges. To this end, this article conducts a comparative analysis of a previously developed application system for transmitting dynamic 3D human movements with a ready-made solution for transmitting 2D video streams in order to provide conference calling services. The network characteristics of the systems were collected and compared. The opportunities that programs currently provide and will provide in the future are examined.Publication Open Access Task Scheduling Problem in Fog Computing Environment with improved Memetic algorithm(Faculty of Engineering, 2026-03) Thang, D.V; Artem, V; Muthanna, A; Vorozheikina, O; Koucheryavy, AThe task scheduling problem in fog computing is one of the key challenges in the development of fog computing within next-generation communication networks. Addressing this challenge requires balancing processing performance with resource constraints while meeting network conditions. Given the distributed and heterogeneous nature, as well as the dynamic topology, optimally allocating tasks to fog nodes is a complex issue. To contribute to solving this problem, we propose a task scheduling method based on an improved Memetic algorithm. The proposed method leverages the strengths of evolutionary algorithms and local search, while incorporating a task restructuring mechanism, to enhance allocation efficiency and task processing in the fog computing environment. Simulation experiments demonstrate that the proposed method outperforms genetic algorithms, Round-Robin, Greedy methods, and the Ant Colony Optimization algorithm in terms of efficiency. This study provides a fresh, simpler approach that aligns with network conditions while still achieving the desired performance.Publication Open Access Analysis of Thermal Performance of Shell and Tube Heat Exchangers: A Correlation and CFD Based Approach(Faculty of Engineering, 2026-03) Ushettige, S.A.P; Wimalsiri, W.K.; Hikkaduwa,H.G.S.Shell and tube heat exchangers are devices which are widely adopted in thermal systems for the transfer of thermal energy due to both performance and reliability factors. Given their application in energy-intensive systems, the design and sizing of these devices have become a rapidly growing field. Traditionally, empirical correlations which were based on experimental results were used for thermal sizing and design. This was replaced by computational fluid dynamics (CFD) modelling given its ability to model and visualize flow, expanding the horizon of possibilities for design and performance optimization. Recently, CFD has been combined with numerical methods such as non-linear leastsquares regression to develop correlations that predict thermal performance based on input design parameters. However, the application of this integrated method for shell and tube heat exchangers is limited. This study will model a single-pass TEMA E-type shell and tube heat exchanger using ANSYS Fluent ®. CFD simulations are used to explore the effect of turbulence on thermal performance by varying both the inlet mass flow rate and the central baffle spacing. Steady state simulations are conducted for four models with six, eight, ten, and twelve baffles. The results of CFD modelling are then combined with non-linear least squares regression in the MATLAB Curve Fitter Toolbox ® to develop four sets of correlations in the form of 𝑁𝑢 = 𝐶. 𝑅𝑒𝑎. 𝑃𝑟𝑏 . Reasonably confident results were obtained in the final fitted data; however, relatively high 95% confidence interval widths were evident for certain fitted coefficients leaving space for improvement in the model. The study highlights that combining CFD with tools such as nonlinear least squares regression aids both engineers and designers in the thermal design process of shell and tube heat exchangers eliminating the need to limit design based on empirical correlations.Publication Open Access Solar Hotspot Detection Using VHDL-Simulated Fixed-Point SVM: A Methodology Toward FPGA Realization(Faculty of Engineering, 2026-03) Fernando, N; Seneviratne, L; Weerasinghe, N; Rathnayake, N; Hoshino, YEarly detection of thermal hotspots in photovoltaic modules is critical to ensuring their efficiency, safety, and longevity. This study presents a complete end-to-end methodology for implementing a fixedpoint Medium Gaussian Support Vector Machine classifier using VHDL for a Field Programmable Logic Array. The approach begins with feature extraction from thermal images of healthy and defective solar panels, which focuses on MPEG-7 descriptors. The study shows that high impact for hotspot detection comes from blue chrominance contrast. A medium Gaussian SVM model is trained in MATLAB and converted to a fixed-point Q1.15 format for hardware compatibility. Key parameters, including support vectors, Lagrange multipliers, bias, and kernel scale, are extracted and verified in a custom Python environment to ensure numerical alignment with MATLAB results. The validated model is then implemented in synthesizable VHDL. It is verified using GHDL and the GNU Tool Kit waveform viewer, confirming bit-accurate hardware behaviour. Results show classification accuracy exceeding 99.3% with negligible performance loss due to quantization. The design achieves deterministic latency through an FSM-based structure and parallel feature processing for a 300-support vector and 222-feature system. This method enables low-power, real-time inference on a UAV-based edge platform, primarily focusing on drones.Publication Open Access Circular Economy Practices in Road Rehabilitation and Development in Sri Lanka(Faculty of Engineering, 2026-03) De Alwis, L. M.; Gunarathna, K A N; Kalugala, C.The integration of Circular Economy principles into road rehabilitation and development offers a sustainable alternative to traditional linear construction practices. In Sri Lanka, where road infrastructure is crucial to economic growth and connectivity, the Circular Economy offers opportunities to reduce reliance on virgin materials, minimise environmental impact, and enhance longterm cost efficiency. This study explored applicable Circular Economy strategies, assessed current implementation practices, identified key challenges, and proposed viable solutions to support Circular Economy adoption in the Sri Lankan Road sector. A mixed-methods approach was employed, combining a comprehensive literature review with data from semi-structured expert interviews and a questionnaire survey of construction professionals. The findings indicate that while awareness of the Circular Economy is growing, its practical application remains limited due to barriers such as the absence of standardized technical guidelines, insufficient government incentives, limited stakeholder knowledge, logistical challenges in material sourcing and storage, and reluctance to shift from traditional methods. Data also highlights substantial potential benefits, including cost savings, reduced construction waste, increased material efficiency, and environmental improvements. Participants emphasized the importance of pilot projects, training programs, and policy support in promoting Circular Economy practices. To overcome existing barriers, the study recommends the development of clear Circular Economy specifications, financial incentives, capacity-building initiatives, and the establishment of centralized recycling infrastructure. These strategic actions can facilitate the transition toward a more circular and sustainable approach in Sri Lanka’s Road construction and maintenance sectors.Publication Open Access Macaranga peltata Leaf Extract Mediated Green Synthesis of Iron Nanoparticles and Their Application in Organic Dye Removal(Faculty of Engineering, 2026-03) Dissanayake D.M.K.N.; Perera M.A.D; Karunaratne M.S.A; Pahalagedara M.NThis study presents an eco-friendly method for synthesizing iron nanoparticles (FeNPs) using Macaranga peltata leaf extract, and evaluate their potential for degrading the organic dye methyl orange (MO). The synthesis exploits phytochemicals in the leaf extract as natural reducing and stabilizing agents. The synthesized FeNPs were characterized using UV-Vis spectroscopy, FTIR, XRD, and SEM, confirming amorphous structure and particle sizes ranging from 34–94 nm. Catalytic activity was evaluated via MO degradation experiments, achieving 85.16% efficiency within 200 minutes. The study demonstrates a sustainable wastewater treatment solution using green nanotechnology.Publication Open Access Developing A Web-Based Augmented Reality Tool For Promoting Sustainable Fashion Consumption(Faculty of Engineering, 2025-09) Fernando D.T.; Methma S.L.K.K.; De Silva R.K.J.This study explores the use of Augmented Reality (AR) as an intervention to promote sustainable fashion consumption among Sri Lankan consumers. It also involves developing a web-based AR tool designed to educate users about sustainable fashion and evaluating its acceptance within the target audience. This research identified that young consumers in Sri Lanka demonstrate a low level of awareness regarding sustainable fashion consumption. Therefore, this study addresses an important gap by analyzing how interactive digital tools can influence consumer education and promote green purchase behaviors. To gather requirements for developing the AR tool, a qualitative research method was employed through focus group discussions with 8 Gen Z participants representing diverse fashion preferences. For validation, the tool was further tested with 30 participants to evaluate usability, engagement, and effectiveness. Nine themes relevant to AR tool development were identified through thematic analysis, which highlighted the awareness about sustainable fashion, patterns of digital learning, and sensitivity to AR capabilities. This study revealed a strong consumer intention to engage with visually dense, socially sharable, and mobile-optimized AR applications. To address these points, a prototype web-based AR platform was designed using MyWebAR platform, alongside real time information on garment sustainability through the scanning of QR codes. The results demonstrate that AR can successfully engage consumers, increase awareness of the environmental footprint of fashion, and enable behavioral change when deployed on familiar social media platforms. The research concludes that interactive, culturally relevant AR tool experiences have strong potential to influence sustainable fashion practice among consumers.Item Embargo From AI Assistance to Critical Thinking: Exploring Cognitive Offloading and Metacognition as Mechanisms within Personalized Learning Environments(Institute of Electrical and Electronics Engineers Inc., 2026) Gunathilake, N; Gamage, A; Rajapakshe, D; Jayasooriya, M; Wisenthige, K; Yapa, C.GThe rapid adoption of AI-assisted learning tools in higher education has completely transformed the undergraduate study system, but empirical evidence on their impact on deep cognition and learning processes is limited. This study investigates the effects of AI-assisted learning tool usage on metacognition, cognitive offloading, personalized learning, and critical thinking among Sri Lankan undergraduates. Using positivism philosophy and a deductive quantitative approach, data were collected from 379 students in computing, management, and engineering subjects through a 35-items, five-point Likert scale questionnaire, and analyzed using PLS-SEM. The findings reveal significant direct, indirect, and moderating relationships among key variables, suggesting that the use of AI-assisted learning tools influences students’ learning regulation, reliance on external support, and development of higher-order thinking. This study provides empirical evidence for the cognitive and psychological effects of AI-assisted learning tools, and helps address an important research gap, and offers practical insights for educators, curriculum developers, and policymakers to use balanced and effective AI integration in higher education.Item Embargo A Comprehensive Approach to Secure, Accessible, and Engaging Voting Systems(Springer Science and Business Media Deutschland GmbH, 2026) Jayasinghe J.A.M.P; Bandara S.Y.T.D; Shabry S.M; Wickramasinghe W.A.R.M.; Rajapakse, K; Silva, NThis research presents a secure and accessible e-voting system for polling booths in Sri Lankan context, to overcome issues with the traditional voting system. It incorporates block-chain for fair vote storage, and homomorphic encryption for privacy preserving computation of results. The identity of voters is confirmed by face recognition, which includes measures to deterring any voting by impostors. Special identification model with multiple digits is beneficial for disabled voters. Public opinion is effectively gauged through sentiment analysis from social media and it puts concerns to rest, thus a whole lot of enhancement in the whole of customer engagement. Ease of use is also assured thanks to a very user-friendly interface which eliminates mistakes a lot with only a little effort generally. Experimental results demonstrate that security is greatly strengthened, transparency and usability are significantly increased traditional procedural integrity is still maintained efficiently.Item Embargo Interactive Sinhala Letter Learning Module for School Children (Grade 1 to 5)(Springer Science and Business Media Deutschland GmbH, 2026) Weerasooriya, K; Udana, I; Jayasinghe, L; Kasiwaththa, J; Rajapaksha, S; Kumari, SSinhala is the native language of most people in Sri Lanka. However, most of the children find it difficult to write Sinhala letters fast and accurately, this may undermine their confidence and affect grades. The primary issue is that the parents usually lack their time in order to assist their children in their studying at home. Few interesting tools also exist to teach children how to write in Sinhala in an interesting and effective manner. To address these issues we have developed the ”Interactive Application of the Sinhala Language to School children (Grade 1 to 5) which is a web based application, to allow children studying in primary schools to enhance their knowledge of the Sinhala language. This app provides children an entertaining and effective method of learning how to write Sinhala letters. The system combines instructions in animation, touch tracing finger tools, hand writing recognition and immediate feedback such that kids can learn Sinhala writing, and the non touch screen users can post their written letters on paper to be analyzed individually as to feedback analysis. The system uses handwriting recognition to provide real-time feedback on accuracy and speed. The system also monitors progress and generates comprehensive reports to help children and parents in identifying areas requiring improvement. The application uses a combination of engaging letter tracing and intensive deep learning which are not present in other learning tools. Additionally, the system will aid parents to mentor their children in education even when they are in charged schedules and also enable children improve their skills in Sinhala writing. We offer to make the learning of Sinhala to school students in Sri Lanka easier, more relevant and interesting.