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2-Tuple Fuzzy Linguistic Model to Evaluate the Risk of Invasive Plant Species
(Department of Statistics & Computer Science, University of Kelaniya, Sri Lanka, 2016) Peiris, H.O.W.; Perera, S.S.N.; Chakraverty, S.; Ranwala, S.M.W.
Management of invasive species can appear to be a complicated and unending task. In order to manage the spread, these species need to be undergone any risk assessment during their introduction. The aim of this study is to evaluate the aggregate risk of Invasive Alien Species (IAS) using invasive attributes. We use the 2-tuple fuzzy linguistic representation to develop the model without loss of information in which occur in ordinary linguistic operators. These risk values are compared with the National Risk assessment scores which are in the form of Linguistic labels. The proposed model is validated using few known noninvasive species in Sri Lanka. The model gives significant predictions and it is found to be a better tracking system for identifying potential invaders than the conventional risk assessment methods.
The 3D atomic scale and electronic structure characterization of novel fcc ruthenium nanoparticles using synchrotron light source
(Faculty of Science, University of Kelaniya, Sri Lanka, 2016) Kumara, L.S.R.; Sakata, O.; Kohara, S.; Song, C.; Yang, A.; Kusada, K.; Kobayashi, H.; Kitagawa, H.
Ruthenium (Ru) is a 4d transition metal that in the bulk adopts hexagonal closepacked (hcp) structure at all temperature ranges, and novel face-centered cubic (fcc) Ru nanoparticles (NPs) have been observed to be more efficient than conventional hcp Ru NPs larger than 3 nm. It has recently attracted much attention as a potential application in removal of car exhausts due to high catalytic activity for CO oxidation and preventing CO poisoning in fuel-cell system. We here report the 3-dimentational atomic-scale structures of fcc and hcp Ru NPs using high-energy X-ray diffraction (HEXRD), Rietveld analysis, pair distribution function (PDF), and reverse Monte Carlo (RMC) modelling. Hard X-ray photoelectron spectroscopy (HAXPES) can provide important information on the influence of NP size on electronic properties. The HEXRD and HAXPES of Ru NPs were performed at BL04B2 and BL15XU at SPring-8, the world largest third-generation (8 GeV) synchrotron radiation facility located in Hyōgo prefecture, Japan. We observed higher stability of the lattice distortion of fcc Ru NPs with increasing particle size. The PDF analysis results show that the structural disordered Ru NPs at short- to intermediate-range atomic distances. The order parameter for fcc Ru NPs decreased with increasing particle size due to the loosely packing atomic arrangement and may explain an origin of higher catalytic activity of fcc Ru NPs. In this study, the observed trend of increasing catalytic activity of fcc Ru NPs was also discussed using their core-levels and valence band electronic structures. This work was partly supported by ACCEL, Japan Science and Technology Agency (JST) and also partly supported by Ministry of Education, Culture, Sports, Science and Technology of Japan (OS: 15K04616).
A Deep Learning-Based Approach for Detecting Duplicate GitHub Issues in Open-Source Repositories Using LSTM
(Department of Industrial Management, Faculty of Science, University of Kelaniya., 2025) Dharmadasa, T. K. R. S.; Rupasingha, R. A. H. M.; Kumara, B. T. G. S.
GitHub is a platform used along with the popular version control tool Git to provide hosting facilities to software repositories. Users can publish GitHub issues to notify the repository contributors about bugs, questions, and feature requests. GitHub hosts open-source repositories that are contributed by developers across the globe. The asynchronous and uncoordinated nature of these contributions in open-source repositories increases the probability of posting duplicate GitHub issues, resulting in redundant efforts. The standard mechanism introduced by GitHub to mark duplicate issues is adding a comment to that issue body mentioning the original issue. Then GitHub will add the corresponding duplicate tag and close that issue. However, due to manual labor required to find duplicates, developers are discouraged from seeking similar issues before publishing a new issue to GitHub. The study’s main objective is to address this problem and propose an automated solution using deep learning algorithms. Our research introduces a novel approach that combines feature extraction and similarity calculations to identify duplicate GitHub issues. The proposed methodology extracted over 4000 GitHub issues covering different programming languages and repositories. After pre-processing, various features were extracted using multiple feature extraction techniques, and semantic similarity metrics such as cosine similarity were utilized to create the feature vector. The feature vector was used with different algorithms like Artificial Neural Network (ANN) and Recurrent Neural Network (RNN) including deep-learning algorithms like Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN). Algorithm results are compared to detect the most suitable approach for detecting duplicate GitHub issues. Based on the different evaluations, LSTM is the better approach resulting in 88% accuracy with the highest precision, recall, and f-measures while giving the lowest error rates. With this proposed methodology, duplicate GitHub issues can be easily detected, reducing the manual work.
A Hybrid Architecture with Efficient Fine Tuning for Abstractive Patent Document Summarization
(Department of Industrial Management, Faculty of Science, University of Kelaniya., 2025) Jayatilleke, N.; Weerasinghe, R.
Automatic patent summarization approaches that help in the patent analysis and comprehension procedure are in high demand due to the colossal growth of innovations. The development of natural language processing (NLP), text mining, and deep learning has notably amplified the efficacy of text summarization models for abundant types of documents. Summarizing patent text remains a pertinent challenge due to the labyrinthine writing style of these documents, which includes technical and legal intricacies. Additionally, these patent document contents are considerably lengthier than archetypal documents, which complicates the process of extracting pertinent information for summarization. Embodying extractive and abstractive text summarization methodologies into a hybrid framework, this study proposes a system for efficiently creating abstractive summaries of patent records. The procedure involves leveraging the LexRank graph-based algorithm to retrieve the important sentences from input parent texts, then utilizing a Bidirectional Auto-Regressive Transformer (BART) model that has been fine-tuned using Low-Ranking Adaptation (LoRA) for producing text summaries. This is accompanied by methodical testing and evaluation strategies. Furthermore, the author employed certain meta-learning techniques to achieve Domain Generalization (DG) of the abstractive component across multiple patent fields.
A Unified Pipeline for Improving Financial Aid Eligibility Predictions in Deep Learning Models
(Department of Industrial Management, Faculty of Science, University of Kelaniya., 2025) Kishanthan, S.; Hevapathige, A.
This paper systematically evaluates the performance of widely used deep learning architectures for financial aid prediction, identifying critical bottlenecks that hinder optimal performance. To address these limitations, we further propose a novel pipeline that enhances deep learning models by incorporating three key components: text vectorization, data equalization, and adaptive feature recalibration. This pipeline improves the models’ representational power and predictive accuracy, offering seamless integration with existing architectures. It significantly boosts performance in predicting financial aid eligibility, providing up to a 145% increase in balanced accuracy and a 45% increase in F1 score.
Abhiram, G. and Munasinghe, R. C. (2018). Development of new master batch mixing cycle for a track producing extrusion compound with lower rejection rate
(Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Thennakoon, T. M. A. D. L.; Withanage, N. S.
As rubber shows inherent viscous and elastic properties, mixing of compounding ingredients is the first and most important step in rubber manufacturing. If mixing does not properly happen, many problems will be appeared in the end product leading to higher rejection. Currently, Rubber compounding industry produces track producing extrusion compounds to make continuous band of tread for military, agricultural and construction vehicles around 98% rejection, due to viscosity. Therefore, the focus of this research was to develop a new master batch mixing cycle by modifying the present conditions maintained during mastication phase, carbon black incorporation phase and dispersion phase to reduce the rejection level of track producing extrusion compound. Hence, the mastication phase rotor speed (30 rpm, 40 rpm, 50 rpm), mastication phase masticate time (60s, 80s, 100s), carbon black incorporation phase rotor speed (30 rpm, 40 rpm, 50 rpm) and dispersion phase rotor speed (30 rpm, 40 rpm, 50 rpm) were changed separately to obtain the optimum conditions for each phase giving better viscosity properties of the compound. The results revealed that, the best batches could be obtained under 50 rpm rotor speed and 80s masticate time in mastication phase; 50 rpm rotor speed in carbon black incorporation phase and 40 rpm rotor speed in dispersion phase. Therefore, the new master batch mixing cycle could be considered as 50 rpm rotor speed and 80s masticate time in mastication phase; 50 rpm rotor speed in carbon black incorporation phase and 40 rpm rotor speed in dispersion phase to reduce the present rejection rate of track producing extrusion compound TR-5237.
Abundance and distribution of microplastics in Muthurajawela wildlife sanctuary and Pamunugama beach, Sri Lanka
(Faculty of Science, University of Kelaniya Sri Lanka, 2024) Sandaruwan, U. A. C.; Vithana, P. V. A. S.; Sithumini, W. E. B. K.; Samaraweera, B. G. K. N. D. B.; Tharani, T.; Gallage, C.V.; Subasinghe, K.; Vidanage., S. P.
Microplastics (MPs), defined as plastic particles less than 5 mm, are increasingly recognized as a global environmental threat impacting marine and terrestrial ecosystems. This study investigates the prevalence, distribution and characteristics of MPs in the lagoon and coastal sediments of Muthurajawela Wildlife Sanctuary and Pamunugama Beach in Sri Lanka, areas interconnected through the Negombo Lagoon. Sediment samples were collected from 14 locations (06 from the Muthurajawela lagoon and 08 from the Pamunugama beach) distributed in both in low-tide line and mid-tide line identified through systematic sampling method. From each location, three replicate samples were collected to form a composite sediment sample and 20g of oven-dried sediment was used for analysis of MPs after performing a density separation on the sieved sample. The abundance, size, and shapes of MPs were examined using a stereomicroscope using “Optica TCB5.0” software. Observed MPs were divided into two size ranges: 5 mm – 1.1 mm and 1 mm – 0.5 mm and defined as “large MPs” and “small MPs” respectively. MPs were divided into five categories of shapes: fragments, filaments, films, foams and pellets. Findings indicated a higher abundance of MPs in Pamunugama Beach sediments (79.3 ± 10.3 MPs/Kg) compared to Muthurajawela lagoon (58.0 ± 10.8 MPs/Kg). In Muthurajawela, smaller MPs were more prevalent (79.87%) than larger MPs (20.12%), with a statistically significant difference (p<0.05; Two-sample T test) while Pamunugama Beach showed no significant difference in the abundance of large and small MPs. The abundance of total MPs was not significantly different between low and mid-tide lines at both study sites suggesting a low spatial variability in abundance (p>0.05; Two-sample T test). The most common MP shape in Muthurajawela was filaments (78.8%), while fragments (61.53%) dominated Pamunugama Beach. The study also underscores the impact of the MV X-Press Pearl ship disaster on Pamunugama Beach, contributing to the higher MP levels observed. MPs in Muthurajawela were primarily filament-shaped, likely sourced from urban wastewater and industrial activities, whereas Pamunugama Beach exhibited more fragment-shaped MPs due to recreational activities and natural fragmentation processes driven by coastal dynamics. These findings provide critical baseline data for long-term monitoring and highlight the need for targeted mitigation strategies. Future research should focus on the ecological impacts of MP pollution, particularly on wetland birds and other wildlife in these regions. Comprehensive studies examining the sources, pathways, and ecological consequences of MPs will further inform conservation efforts and policy decisions, ultimately contributing to the protection of Sri Lanka's unique coastal and wetland ecosystems.
Abundance and distribution pattern of Aedes aegypti and Aedes albopictus in selected urban, sub-urban and rural areas of Gampaha District, Sri Lanka
(Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Dalpadado, C. P. R. D.; Amarasinghe, L. D.
The abundance and distribution of Aedes aegypti and Aedes albopictus, vectors of dengue fever, were determined at six localities in Gampaha District, which is the district with the occurrence of second highest number of dengue cases during last five years. Negombo and Wattala areas were selected to represent urbanized communities, Gampaha and Attanagalla to represent sub-urban communities and Dompe and Divulapitiya were selected for the rural communities based on population density. Percentage of premises infected with Aedes larvae (Premise Index) and the number of positive containers for 100 premises inspected (Breteau Index) were used as a proxy to determine the abundance of vectors. Larval collections were done monthly during April 2016 to June 2018 using random sampling technique for minimum 100 houses within a radius of 300 m. Potential breeding places in each site were identified and categorized accordingly. Out of 7916 premises examined, 1011 (12.8%) premises were found to be positive for Aedes mosquitoes. Among them 10.1% and 89.9% were found to be positive for Ae . aegypti and Ae . albopictus, respectively . Ae . aegypti was mostly prevalent in highly urbanized MOH areas (73%) while it showed low abundance in sub urban (21%) and rural (6%) areas. On contrary, abundance of Ae . albopictus was highest in sub-urban areas (47%) and lowest in urban areas (18%). Premise index (PI) for Ae . aegypti in urbanized areas were significantly higher than that of sub-urban (F=9.13, p<0.05) and rural areas (F=15.49, p<0.05) in Gampaha District and there was no significant difference (F=4.04, p>0.05) between PI of Ae . aegypti in sub urban and rural areas. The PI of Ae . albopictus in sub-urban areas was significantly higher than that of urban areas (F=15.43, p<0.05). There was no significant difference (F=1.44, p>0.05) between PI of Ae . albopictus in sub-urban and rural areas. Similarly, there was no significant difference between mix indices for Ae . aegypti and Ae . albopictus in Gampaha district (p>0.05). There was a strong correlation between the Breteau Index and the number of dengue patients reported in urbanized areas (r<0.5). Higher correlation was recorded with Ae . aegypti than Ae . albopictus. Therefore, occurrence of dengue epidemics are strongly correlated with Ae .aegypti indices in city areas of Gampaha District and present study suggests that Stegomyia indices can be used as a proxy to determine dengue transmission risk.
Abundance and microplastic characterization found in the mud crab Scylla serrata inhabiting Negombo Lagoon, Sri Lanka
(Faculty of Science, University of Kelaniya Sri Lanka, 2023) Dias, B. C. G.; Amarathunga, A. A. D.; De Silva, D. S. M.; Sivyer, D. B.; Maddumage, M. D. S. R.
Microplastics (MPs) are tiny plastic particles less than 5 mm in size. The danger imposed by MPs continues to rise in the world due to an increase in anthropological pollutants in the environment. The tremendous socioeconomic value and biodiversity of the lagoon have been threatened by a significant accumulation of plastics, particularly MPs. MPs have many negative impacts on the fauna. Herein, the high adsorption capability of MPs increases the toxicity of contaminants as well as oxidative stress that may lead to damaging cell membranes of fauna. Here, we report the investigation on the abundance of MPs in the digestive tract and gills of the mud crab species Scylla serrata, which is a prominent edible food source of humans. We collected fifty two (N = 52) individuals of mud crabs from three crab trapping sites in the Negombo Lagoon, Sri Lanka during November 2022 to March 2023. The gills and digestive tract of the crabs were extracted and digested in KOH, and subsequently the putative MPs were separated and imaged using a stereomicroscope (VWR VisiScope 360) for characterization. In the analysis, a total of 455 MP particles were detected in the crabs, out of which, 187 (41.10%) were in the gills and 268 (58.90%) were in the digestive tracts. The average MP abundance in the gills was 0.70 ± 0.52 items per gram, while that in the digestive tracts was 0.71 ± 0.52 items per gram. The most abundant shapes of MP particles were fibers in the gills (54.01%) and in the digestive tracts (85.07%) followed by fragments and films. Further, the prevailing colours of the MPs were blue, transparent, red, black, and purple. Herein, the digestive tract had the highest concentration of MPs in blue (47.38%), whereas the majority of the MPs found in the gills were transparent (51.8%). The range of MP sizes in the crabs was also determined. The most frequent size range in the gills and digestive tracts were 0.002-0.25 mm (39.5%), and 1.0-5.0 mm (48.8%) respectively. Despite the fact that the current study offered details on the presence of MPs in the gills and digestive tract of the mud crab species Scylla serrata inhabits in the Negombo Lagoon, it also serves as a benchmark for the quick detection of MPs in mud crabs in the lagoons of Sri Lanka.
Accelerate business growth by synergizing emotional intelligence
(Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Subashini, K. K. P.
“Emotions drive people, people drive performance”. Emotional Intelligence is a critical success factor for the sustainable business growth on which professionals need to concentrate. Emotional intelligence is an invisible skill, which can be developed through learning, training and practicing. To be a part of successful, satisfied, high customer delight team, it is important to have positive, effective interpersonal skills as well as high emotional intelligence empowerment. Research has shown that every emotion has a function. Experts opine that “People buy relationships, not products”. To accelerate business growth, professionals need to pay attention of the emotions of the clients. The objective of this paper is to identify the factors that affect the business growth. We used random sampling techniques to collect data. Then we analyzed the data by using statistical tools. We first setup a forum for software professionals to discuss the challenges, limitations and success factors. We then conducted an online survey based on the findings from forum and literature review. Through this, we identified more than 30 challenges and several best practices. We further conducted a set of face-to-face interviews with the subject matter expertise like customer relation managers and sales teams to identify a suitable set of solutions, and finally developed a framework. According to the result shown in the survey, clients are willing to have emotional bond with the development team. Further, 80% of the professionals agreed that emotional connection is one of the main factor for the project success. It has also shown that 70% of the people state that emotional intelligence is a skill, which needs to be trained by the expert for better work environment. 75% of the experts state that emotional intelligence is needed for good personal relationship. 60% of the professionals agreed that empathy is the major factor, which help to have a good work environment. It also found that technical team has to understand the power of emotional intelligence to have good business growth in the organization.
Accelerating Meta-Learning with the Enhanced Reptile Algorithm for Rapid Adaptation in Neural Networks
(Department of Industrial Management, Faculty of Science, University of Kelaniya., 2025) Shree Smeka J.; SheejaKumari V.; Vijaya Raj M.; Santhosh Kumar S. P.; Angalaeswari S.
Reptile is an innovative meta-learning approach that improves the process of neural networks training across diverse tasks. Reptile differs from the preference gradient strategies. It searches for a model weight vector which can enable a model to learn a new set of tasks with a small number of weight updates. This is accomplished via a first-order optimization process which makes it less intricate than other strategies like model-agnostic meta-learning MAML. Reptile is said to sample a number of tasks and then trains the model on each of the tasks via performing a series of a few gradient steps, systematically updating the model towards the average gradient direction across all the tasks. This enables the model to generalize well with new tasks trained with few iterations, thus proving beneficial in few-shot learning. Reptile enables faster adaptation of the model by focusing on the learning of better initial parameters thereby lowering computational overhead and the training duration. The algorithm is noted for its ability not only to learn but also to adapt itself to new tasks in a short period of time, which greatly extends the scope of its application, especially in areas where data is scarce. Examples of these areas are robotics, personalized advertisements, and decision-making approaches that need to operate in real time. Reptile Algorithm builds good on gradient-based approaches and can spearhead volumetric applications of meta reasoning by being exceptionally efficient, scalable and less computationally intensive.
Accelerating the rate of convergence of some efficient schemes for two-stage Gauss method
(Faculty of Science, University of Kelaniya, Sri Lanka, 2016) Chamaleen, D.B.D.; Vigneswaran, R.
The non-linear equations obtaining from the implicit s – stage Runge-Kutta methods have been solved by various iteration schemes. A scheme has been developed, which is computationally more efficient and avoids expensive vector transformations. The rate of convergence of this scheme is examined when it is applied to the scalar test differential equation 􀀒􀀢 = 􀀣􀀒 and the convergence rate depends on the spectral radius 􀀤[􀀘(􀀦)] of the iteration matrix 􀀘(􀀦), where 􀀦 = ℎ􀀣 and ℎ is the step-size. In this scheme, supremum of a lower bound for 􀀤[􀀘(􀀦)] is minimized over the left half 􀀦- plane with the constraints requiring super-linear convergence at 􀀦 = 0 and 􀀦 → ∞ .Two new schemes with parameters are obtained for the two-stage Gauss-method. Numerical experiments are carried out in order to evaluate and compare the efficiency of the new schemes and the original scheme. Consider an initial value problem for stiff system of ordinary differential equations 􀀒􀀢 = 􀀬􀀭􀀒(􀀟)􀀮, 􀀒(􀀯) = 􀀰, 􀀬: ℝ􀀐 → ℝ􀀐. An s-stage implicit Runge-Kutta method computes an approximation 􀀒􀀳􀀴􀀜 to the solution x (􀀟􀀳􀀴􀀜) at discrete point 􀀟􀀳􀀴􀀜 = 􀀟􀀳 + ℎ by 􀀒􀀳􀀴􀀜 = 􀀒􀀳 + ℎ Σ 􀀛􀀶 􀀷 􀀶 􀀸􀀜 􀀬(􀀔􀀶 ), where 􀀔􀀜 ,􀀔􀀙 ,…,􀀔􀀷, satisfy sn equations 􀀔􀀶 􀀸 􀀒􀀳 + ℎ 􀀺 􀀯􀀶􀀻 􀀷 􀀶􀀸􀀜 􀀬􀀭􀀔􀀻􀀮, ), 􀀼 = 1,2, . . . , 􀁀. 􀁁 = 􀁂􀀯􀀶􀀻􀁃 is the real coefficient matrix and 􀀛 = [􀀛􀀜 ,􀀛􀀙 ,…,􀀛􀀷]􀁄 is the column vector of the Runge-Kutta method. Let 􀀔 = 􀀔􀀜 ⊕ 􀀔􀀙 ⊕ … ⊕ 􀀔􀀷 ∈ ℝ􀀷􀀐and 􀁇(􀁈) = 􀀬(􀀔􀀜) ⊕ 􀀬(􀀔􀀙) ⊕ … ⊕ 􀀬(􀀔􀀷) ∈ ℝ􀀷􀀐. Then the above equation in 􀀔􀀜 ,􀀔􀀙 ,…,􀀔􀀷 may be written by 􀁈 = 􀁉 ⊗ 􀀒􀀳 + ℎ(􀁁 ⊗ 􀁋􀀐)􀁇(􀁈), where 􀁉 = (1,1, … ,1)􀁄 and (􀁁 ⊗ 􀁋􀀐) is the tensor product of the matrix 􀁁 with 􀀑 × 􀀑 identity matrix 􀁋􀀐. The efficient scheme, which has been already proposed, is given by [􀁋􀀷 ⊗ (􀁋􀀐 − ℎ􀁌􀁍)]􀁎􀁏 = (􀁐 ⊗ 􀁋􀀐)(􀁉 ⊗ 􀁑􀀳 – 􀁈􀁏) + (􀁓 ⊗ 􀁋􀀐)( 􀁉 ⊗ 􀁑􀀳 – 􀁈􀁏􀁔􀀜) + ℎ(􀁕 ⊗ 􀁋􀀐)􀁇(􀁈􀁏) + ℎ(􀀌 ⊗ 􀁋􀀐)􀁇(􀁈􀁏􀁔􀀜), 􀁖 = 1,2, …, In this scheme, supremum of a lower bound for 􀀤[􀀘(􀀦)] is minimized over ℂ􀁔, where ℂ􀁔 = {􀀦 ∈ 􀁙 /􀀌􀁉 (􀀦) ≤ 0 } with the constraints 􀀤[􀀘(􀀦)] = 0 at 􀀦 = 0 and 􀀤[􀀘(􀀦)] = 0 at 􀀦 → ∞. The parameters for the two-stage Gauss method are obtained and Numerical experiments are carried out.
Acceptance of ICT-Enabled Services Among Bangladeshi Farmers
(Department of Zoology, University of Kelaniya, Kelaniya, Sri Lanka, 2014) Quarmal, S.B.
This paper is aimed at presenting a proposed work that focuses on the decision-making process regarding the acceptance of ICT-enabled services among Bangladeshi farmers. For this purpose, an Artificial Society Model (ASM hereafter), introduced by the authors, is being used. This psychology-oriented ASM of decision-making deals with knowledge-based decision-making process. It consists of a set of agents that represents groups of people who respond similarly to certain problem. The agents are characterized by the extent of knowledge that they have on the problem. The knowledge of an agent is expressed by a mathematical function. Thinking process of the agent is simulated by using a linkage model of cognitive psychology. A message is formed by the agent, based on the knowledge function and the conclusion (decision) of the agent on the given problem, which is also expressed mathematically, and is transferred to another agent and modifies the knowledge function of the agent that receives the message. As a result, the model enables to simulate dynamics of decision making processes in society. Such modeling helps us to understand various natural and social phenomena such as the issue discussed in this article, i.e. decision-making process regarding the acceptance of ICT-enabled services among Bangladeshi farmers.
Activation of wood biochar and red brick using natural coconut vinegar
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Malka, U.K.M.; De Silva, R.C.L.; De Silva, D.S.M.; Chandrajith, R.
Number of studies have been carried out to determine the efficiency of strong oxidizers in activating natural raw materials used in low cost water purification processes. However, rural communities find it difficult to acquire most of such chemicals. Therefore, this study was aimed to determine the ability of natural coconut vinegar, which is a common domestic acidic solution, in activating abundantly available potential water purifying materials to reduce calcium (Ca2+) ions from water, further reducing the water hardness. In this study mature barks of Glyricidia (Glyricidia sepium), Gadumba (Trema orientalis) and Ipil Ipil (Leucaena leucocephala) were collected and air dried. These were carbonized (400-450 °C) in a closed vessel (2 hours) to produce biochar. Both biochar and brick particles in the range of 2.0-5.6 mm were selected for the analysis. For the activation these samples were soaked in natural coconut vinegar (biochar/brick: vinegar, 1:2 V/V) for 24 hours and completely dried in an oven (120 °C) for 3 hours. Laboratory scale glass columns (2 cm in diameter) were used to calculate Ca2+ adsorption and retaining capacities. Filtrates were analyzed for Ca2+ using flame photometer. Ca2+ adsorption and retaining capacities of each material were calculated per unit bulk volume of the material. Each test was duplicated, and the average was recorded. Untreated red brick and biochar of Glyricidia, Gadumba, Ipil Ipil showed Ca2+ adsorption capacities of 0.44, 0.30, 0.31, 0.27 mg cm3 and retaining capacities of 0.19, 0.01, 0.02, 0.02 mg cm-3 respectively. Activated red brick and biochar of Glyricidia, Gadumba and Ipil Ipil showed Ca2+ adsorption capacities of 0.76, 0.58, 0.68 and 0.63 mg cm-3 and retaining capacities of 0.25, 0.20, 0.23 and 0.15 mg cm-3 respectively. Increase in Ca2+ adsorption and retaining capacities were observed in all the materials tested after activation with vinegar. Further studies are continued to use the vinegar activated natural materials in a low-cost domestic drinking water purification process.
Acute toxicity of formaldehyde on the ornamental fish, Cyprinus carpio (koi carp) fingerlings
(Faculty of Science, University of Kelaniya Sri Lanka, 2024) Rathnayaka, E. M. S. P.; Epa, U. P. K.
The ornamental fish trade is a multibillion-dollar sector that involves more than 125 countries, including Sri Lanka. Formalin, 37% formaldehyde, is widely used in the ornamental fish industry as a prophylactic measure or therapeutic purposes. It is usually used to treat ectoparasites that reside on the body surface or gills of fish, and it is also used as a fungicide for fish eggs. Chemotherapeutic agent usage has been criticized because the indiscriminate usage of chemicals like formalin may cause severe risks to both fish and human health and the environment. The toxicity of chemicals to fish must be decided prior to using any chemical to fish as a therapeutic agent for their diseases. A 96 h acute toxicity test was conducted to determine the median lethal concentration (LC50) of formalin on Cyprinus carpio (Cyprinidae) fingerlings. Experimental fish were exposed to a static bath in 4 L glass aquaria with formalin concentrations of 50, 55, 60, 65 and 70 mg L-1. Seven fingerlings were added to each tank for the acute toxicity test, and glass aquaria were continuously aerated during the test. The control experiment was conducted using de-chlorinated tap water. All five treatments and the control experiment were triplicated. During formalin exposure, fish behavior was observed. The Number of fish deaths was recorded in each concentration separately and probit analysis was conducted to determine the 96-h LC50 value of formalin. Fish behavior changes were investigated during the acute toxicity test. Fish were aggregated near the aeration, erratic swimming with fast movement, fast opercula beating, and fast opening and closing of the mouth, excess mucus production, opercula beating frequency reduction, slow swimming and jumping-like behavior were observed until the beginning of the first death. Mucus accumulation on the body surfaces and gill filament was recorded on dead fish. The gills of the dead fish were damaged and toxicity symptoms were observed. The 70 mg L-1 concentration was the lethal concentration for C. carpio fingerlings in less than 24 h. The LC50 value of formalin on C. carpio fingerlings at 95% confidence level was 55 mg L-1 for 96 h. It was concluded that acute exposure to formaldehyde causes lethal toxic effects on C. carpio fingerlings. Formalin must be used with due care and management in aquaculture practices.
Adaptive green time allocation method for traffic congestion based on cell transmission model and genetic algorithm
(Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Priyasad, H. A. D.; Kulatunga, D. D. S.
Traffic congestion is defined as a physical phenomenon relating to the manner in which vehicles impede each other’s progression as demand for limited road space approaches full capacity. This makes trip time longer and increasing queuing. Also it causes serious problems for the day to day lives of people, massive financial and man-hour loss, environment pollution, some diseases etc. In Sri Lanka, traffic congestion in a given area occurs for many reasons. The main reason is that the demand of road does not match to road capacity. In Sri Lanka, although an increase of 10% per year road demand is expected, it can increase road capacity by around 2% to 3% per year. Other important reasons are the existing traffic control system and traffic intersections. Traffic control systems play a central role of traffic management in Sri Lankan cities. Existing traffic light system mainly controls the traffic light change in constant cycle time. But road conditions in a given area vary day by day. If the traffic control system does not deal with these variations, then traffic control system will create bottlenecks and delays. Therefore, the control of traffic requires adequate adjustments to these variations. This research focused on studying and applying cell transmission model to dynamic traffic signal controlling procedure. Basic cell transmission model is used to model the dynamic changes of vehicular traffic flow and to estimate the total delay of vehicles in a given region within a given time interval under different green time allocations. To find an optimal signal timing plan, the Genetic Algorithm is used. The proposed model is applied with certain assumptions to find an optimal time plan to a signalized intersection in main Kandy - Colombo road which has heavy traffic congestion in the morning hours in weekdays. A section of this region is selected to minimize the total delay and to find an optimal dynamic time plan for the signal lights analyzing the actual data collected in this region using four video cameras. The results are compared with the existing pre-timed signal time plan and the corresponding total delay. It is observed that the proposed dynamic signal timing plan will reduce average delay by 6.2675% and it can be proposed as an alternative for the existing system.
An Adaptive Histogram Equalization Algorithm for Enhance Mammograms
(Department of Zoology, University of Kelaniya, Kelaniya, Sri Lanka, 2014-06) Amarasinghe, A.S.; Abeysooriya, D.P.
Breast cancer is one of the leading cancers in the female population and most of them are lethal; to save lives breast cancer should be identified in its early stage. In Sri Lanka 25% of the detected cancers are recognized as breast cancers in each successive year between 2000 to 2005. Mammography is the most successful method to diagnose breast cancers. Mostly mammograms are poor quality images, and doesn‘t provide any hard evidence to diagnose cancers although it has the accuracy of 80% - 90%. And this is where the mammogram enhancement is essentially needed. Among various image enhancement techniques, histogram equalization is the most convenient method to enhance images. But unfortunately many prevailing histogram equalization techniques are not suitable for mammogram enhancement, because they can‘t accurately separate noise from the image. Detecting cancers in a Mammogram is rather delicate process which needs fairly controlled image enhancement with noise reduction. The proposed histogram equalization technique can control the amount of enhancement and it intelligently separates the noise from the interested regions and enhances the suspicious areas. Many histogram equalization methods are available to enhance images. But the common problem with all these algorithms is they did not concern about the actual intensities of the pixels at all. In fact, this leads the whole image enhancement into failures by over enhancing the images. However, lack of controllability is the major obstacle to use histogram equalization in mammogram enhancement. Actual intensities of the pixels must be contributed to the process of enhancement to control the amount of enhancement and prevent destroying the valuable information. The proposed algorithm uses a set of candidate intensities to pick the most appropriate intensity for the enhancement just like a genetic algorithm. Newly taken mammograms were used to experiment the power of enhancement of the algorithm. The image samples were taken from the Karapitiya hospital, Galle, Sri Lanka, with the authorization from the Director there. The major concerns were how well the algorithm can reduce the noise and highlight the cancerous areas of the images. Obviously this enhancement must assist the observers to find hard evidence to detect cancers. Following shows a mammogram image before and after the enhancement.Identifying a breast cancer is a tough job and it needs years of practice and some sophisticated technology. But still 10% of breast cancers are missed by radiologists. This happens mainly due to noise of the images and complex overlying and underlying structures in the cancer images. Almost every Mammogram is a poor quality image which doesn‘t provide enough hard evidence to pursue and diagnose cancers. This research led to produce an image enhancing algorithm which can be used to enhance mammograms to detect early stage breast cancers to support and assist in medical treatments.
Adding Commonsense to Robotic Application Using Ontology-Based Model Retraining
(Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka, 2022) Pradeepani, M. K. T.; Jayawardena, C.; Rajapaksha, U. U. S.
In terms of the level of technological capability in the world today, the use of automated robotics is common in various fields. There are large projects going on in many industries that collaborate between robots and other robots, as well as humans and robots. In hospital environments, care for people with medical needs and their needs and used to make appropriate suggestions to their problems. Robots can also be found in certain areas that can respond quickly as an emergency rescue agent. Furthermore, robots, which can be seen in the hotel industry as waiters and as farm assistants in agriculture, have a great tendency to be used as multi-tasking agents in many fields. In each of these areas, robots must co-operate with humans. In that situation, the importance of the exchange of mutual knowledge between robots-robots and between humans-robots comes into the picture. What matters here is not only the quantitative vastness of knowledge but also the ability to understand each other in the same medium. Although the common sense that people need in their day-to-day work is completely obvious to humans, the commonsense knowledge domain needs to be implanted in robots. Whatever concept is defined for adding commonsense to robotics, it should be a consistent concept that can be logically constructed so that it can be understood by a machine. As will be discussed later in the paper, different methods have been used in various related works to add a different kind of domain knowledge to robotics. The objective of this paper is to provide an improved retrained model for robotics in order to give them the ability to act more human-like when performing tasks. By using the proposed model robots are able to answer the incomplete command or inquiries related to a given context. One of the objectives of this work is to use the ontology-based, commonsense-support existing knowledge base as a mechanism to retrain and build a new model.
Addressing climate change in Sri Lanka in light of the Human Rights Law: legal analysis
(Department of Zoology and Environmental Management, University of Kelaniya, 2015) Fernando, N.; Bogahawatte, I.
Adoptability of Chaos Engineering with DevOps to Stimulate the Software Delivery Performance
(Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka, 2023) Arsecularatne, Merishani; Wickramarachchi, Ruwan
The efficiency of the business processes has a major impact on improving the productivity of organisations. Many organisations use IT-related tools, primarily software, to enhance the efficiency of their business processes. Therefore, timely and reliable delivery of software products has become a top priority. As a result, advancing the concept of “Agility”, organisations implement DevOps practices. However, maintaining the quality of the software delivery service has become an issue due to several challenges related to the implementation of DevOps. Hence, this study was conducted with the aim of understanding the DevOps-related challenges and how “chaos engineering” can be applied along with DevOps to address those challenges. The practice of "chaos engineering" contributes to the reduction of chaos. A systematic literature review was conducted to investigate the concept of “chaos engineering” and the challenges that DevOps-implemented organisations face. Later, a qualitative study was conducted to see how chaos engineering practices can be used to address the identified DevOps challenges. Based on the thoughts and views of the industry experts who participated in this study, it was revealed that implementing chaos engineering with DevOps helps organisations address most of the DevOps challenges both directly and indirectly. Also, the study suggests a methodology to implement chaos engineering with DevOps within organisations to successfully overcome DevOps-related challenges.