RESCON 2022

Permanent URI for this collectionhttps://ir.lib.pdn.ac.lk/handle/20.500.14444/5952

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Development and application of computer vision-based touchless HMI system for ATM systems in COVID-19 pandemic
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Supunsara, M.G.D.; Indunil, O.R.D.; Rathnayake, A.M.B.; Vidanapathirana, A.C.; Thevathayarajh, T.
COVID-19 is a pandemic that is spreading rapidly worldwide. Direct contact with an infected individual is one form of transmission. This spread has a more prominent possibility in public areas such as ATMs (Automatic Teller Machines) that people use by touching. The spread would be much more significant if an infected person used such products. This research aims to analyze and convert a traditional touch-based ATM system into a touchless computer vision-based system. A new HMI (Human Machine Interface) application was developed for the system to be a more gesture-friendly interface to interact. The new system was able to replace the touch base operations of the old system with hand gestures. A separate health- checking unit was also developed with the touchless computer vision-based system. When an individual entered to use these systems, the health conditions of the person were checked by the health check unit. The unit mainly checks each individual's body temperature, saturated O2 level, and pulse rate. Next, if the users' health data is normal, the individual can proceed to use the HMI ATM application. The data gathered by the health check unit was sent to a cloud server so these data could be stored and used to analyze the health conditions of the people using these systems for a certain period. A mobile application was also developed to gather user data on who uses the device and integrate health check data for each individual. This prototype displayed an ecosystem for integrating the health check unit and the touchless ATM application.
Rainbow vertex connection number of some ladder-type graphs
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Dewananda, W.D.D.P.; Perera, K.K.K.R.
A vertex-coloured graph G is said to be rainbow vertex-connected if every two vertices of G are connected by a path whose internal vertices have distinct colours. The rainbow vertex-connection number of a connected graph G, denoted by rvc(G), is the smallest number of colours that are needed to make G, a rainbow vertex-connected. When sending messages in a cellular network, each link between two vertices is assigned a separate channel. The rainbow connection numbers are used to find the required minimum number of separate channels. In this work, rainbow connectivity numbers on some ladder-type graphs were considered. Ladder-type graphs can be categorized as simple Ladder graphs, Roach graphs, Circular ladder graphs, Triangular ladder graphs, Diagonal ladder graphs and Circular, triangular ladder graphs. Most research has been done on the rainbow vertex connectivity number of pencil graphs, wheel graphs, star graphs, a cartesian product of two graphs, etc. Only a few types of research were available in the literature about ladder and Mobius ladder graphs. In this study, a simple ladder graph and a Roach graph were considered and derived formulae for the rainbow connectivity number of those graphs. We obtained the rainbow vertex connection number of the ladder graph Ln with order 2n as n – 1 and rvc(G) of a Roach graph R (2n, 2k), when, n = 1, rvc(R(2n, 2k)) = k, and rvc(R(2n, 2k)) = 2n for n ≥ 2 and k = 2, ... , 2 + (n − 1) and rvc(R(2n, 2k) = k + (n − 1) for k ≥ 2 + n, n ≥ 2.
Central node identification and cost-effective routing system for garbage collection network
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Dewanthi, K.A.T.; Perera, K.K.K.R.
Environmental pollution is one of the most severe global challenges. It increases gradually and causes a grave impact on living organisms, including human beings. Therefore, waste management is a common issue in all developing countries. Colombo is Sri Lanka's most populated city that faces the biggest garbage problem than other cities. This research focuses on the Colombo municipal council area as it is a highly environmentally polluted city in Sri Lanka. The Colombo municipality area divides into six main administrative districts D1, D2A, D2B, D3, D4, D5, and each administrative district is divided into municipal wards. One municipal ward consists of several locations and streets for collecting garbage. Google map and Colombo municipal council website are used to find garbage collection places, and python software is used to construct a garbage collection network as an undirected graph, where each node represents a location. Each edge represents a path between two locations. In this study, centrality measures such as betweenness, closeness, degree, and eigenvector centrality measures are used to find central locations of the network. After calculating centrality measures, central nodes can be identified by choosing the highest closeness centrality values of the garbage collection network (GCN). Then central nodes of the GCN belonging to each municipal ward can be identified. By identifying central places, some machines or recycling trucks can be placed in those central places to deposit the waste. Those central locations help find the cost-effective route that could reduce the cost and collection time of the garbage collection procedure. The weighted graph was constructed by assigning average garbage amounts for the edges. Collected garbage weights, betweenness centrality and degree centrality, are used to identify the shortest garbage routings between central nodes in each municipal ward. Garbage collection trucks can use this shortest path in order to reduce their fuel cost and collection time.
Upper embeddability in terms of boundary walks
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Caldera, P.A.D.S.P.; Almeida, S.V.A.; Wijesiri, G.S.
Topological graph theory is the branch of graph theory that investigates graphs as topological spaces and the embedding of graphs in surfaces. An embedding of a graph 𝐺 into a surface is a representation of the graph on the surface such that the edges only intersect at their shared vertices. If each face of the embedded graph is homeomorphic to an open disk, the embedding is called a 2-cell embedding. The maximal genus of a graph 𝐺 is the largest integer 𝑛 such that 𝐺 can be 2-cell embedded into a connected sum of 𝑛 tori. An embedding of the graph corresponds to a rotation system that we impose on the graph, and to each rotation system, we associate a set of boundary walks. A boundary walk corresponds to a walk around the border of the face of the embedding and is made up of directed edges in the graph. In this research, the relationship between the maximal embedding genus of a graph 𝐺(𝑉, 𝐸) and the number of boundary walks 𝐵 needed for this embedding was studied with respect to some rotation system. 2-cell embeddings of hypercube and complete graphs were studied, and the findings have been generalized to any simple connected graph. More specifically, we characterise the upper embeddability of a simple connected graph 𝐺 in terms of the number of boundary walks corresponding to a specific rotation system of 𝐺. That is, a graph 𝐺 is upper embeddable if and only if there exists a rotation system that generates either a single boundary walks if |𝐸| − |𝑉| is odd or two boundary walks if |𝐸| − |𝑉| is even. As a corollary, we derive the inequality, 1 ≤ 𝐵 ≤ |𝐸| − |𝑉| + 2.
Assignment problem with fuzzy linear programming
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Welgama, C.R.; Rodrigo, W.N.P.
An assignment problem is a particular case of a transportation problem where the objective is to assign several resources to an equal number of activities to minimize the total cost or to maximize the total profit of allocation. Hungarian algorithm is applied to solve the assignment problem with minimization or maximization problems. If there is an assignment problem with at least two or more objective functions, then there are conflicting objective functions to determine the optimal assignment schedule satisfying all the objective functions and constraints represented in the mathematical model. The Multi-Objective Fuzzy Linear Programming Problem in which all the parameters and variables are represented by fuzzy numbers is known as the Fuzzy Linear Programming Problem. A fuzzy number is characterized by a membership function. Various shapes of membership functions that can be applied to real-world planning are linear, nonlinear, triangular and trapezoidal. This study proposes the Multi-Objective Fuzzy Linear Programming Problem to solve an assignment problem with conflicting objective functions. The linear membership function is used to formulate the fuzzy constraints for the assignment problems. A hypothetical example is used to compare the Hungarian algorithm with the Multi-Objective Fuzzy Linear Programming algorithm. In this study, two problems are solved, where one with an objective minimization function and the other with a maximization objective function solved by applying the Hungarian algorithm. The optimal schedule obtained for the minimization problem is used to obtain the optimal solution for the maximization problem and vice versa. Then, the same problem is solved using the Multi-Objective Fuzzy Linear Programming algorithm to determine the optimal schedule and optimal solutions for maximization and minimization assignment problems. As a result, a feasible schedule and optimal solutions for maximization and minimization problems are obtained by applying the Multi-Objective Fuzzy Linear Programming algorithm.
Time series analysis of crime data of Anuradhapura district, Sri Lanka
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Amarasinghe, R.K.R.K.; Varathan, N.
The global incidence of crime has grown dramatically in recent decades. A similar condition prevails in Sri Lanka, and according to the crime statistics of Sri Lanka Police, about 55,000 crimes are reported annually. Among them, a considerable proportion is occupied by property-related crimes. This study focuses on analyzing property-related crimes that occurred in the Anuradhapura District in the North- Central Province of Sri Lanka. The monthly property crime data has been collected from the police records of Anuradhapura Police Station from January 2003 to December 2019. The data has been analyzed using two different statistical techniques: Box-Jenkins’ Autoregressive Integrated Moving Average (ARIMA) procedure and the Exponential smoothing techniques (Holt’s model and Holt-winters model). Moreover, Akaike Information Criterion, Bayesian Information Criterion, and Mean Square Error were considered to identify the best-fitting model. Results revealed that ARIMA (0, 1, 1) model has higher fitting and forecasting accuracy than Holt’s model and Holt-winters model for the monthly property crime data. This study may be useful for the government, especially the police authority and policymakers, to analyze the crime status of the country, anticipate the increased risk, and make predictions accordingly. Further, it can be used to determine the effectiveness of current policies against criminal offences and make appropriate adjustments to create a safer environment for society and, ultimately, a safer country.
Enhanced oil recovery using one-dimensional nanoparticles
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Sahabandu, C.W.; Dewasurendra, M.
Enhanced Oil Recovery (EOR) is based on three stages; primary, secondary, and tertiary oil recovery processes. In the primary oil recovery process, the natural pressure of the reservoir is used, and in the secondary process, water or gas is injected to enhance the oil recovery. The injection of nanofluids into the oil reservoirs is a recent approach to chemical flooding in the tertiary process. Unlike conventional EOR techniques used in the primary and secondary stages, it has the potential to produce an extra portion of oil. Aluminium oxide, magnesium oxide, silicon dioxide, carbon nanotubes, bacterial cellulose nanocrystals, graphene oxide, and clay materials can potentially be used in nano flooding. This study was carried out to compare the performance of selected one-dimensional nano powders (metallic oxides) for EOR, which are aluminium oxide, magnesium oxide, and silicon dioxide, by dissolving 0.4% of each nano powder into the brine (salted water: since it helps to reduce the dynamic interfacial tension) separately. A new mathematical model was built to find the saturation of nanofluids in the fingering phenomenon for the inclined oil layer. The fingering phenomenon occurs during the second and third oil recovery processes when a fluid contained in a porous medium is displaced through some other of lesser viscosity, as opposed to normal displacement of the entire front. Second-order approximate solutions for saturations of nanofluids for inclination angles 0⁰ and 10⁰ were obtained when the least squared residual error occurs using the Method of Directly Defining the inverse Mapping (MDDiM), which is a novel technique to solve nonlinear differential equations. The results revealed the highest saturation from the brine mixed with aluminium oxide compared to others and also noted that the mixture with magnesium oxide gives the lowest saturation. Since the oil recovery factor is directly proportional to the saturation of the injective fluid, we can conclude that the brine with aluminium oxide benefits the EOR.
Impact of elections on predicting stock market closing prices of Sri Lanka
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Hulangamuwa, R.R.W.G.B.M.K.B.; Dissanayake, R.B.N.
Accurate prediction of closing stock market prices during elections is important for investors. This study examined how the national (presidential and parliamentary elections) and provincial council elections influenced the prediction of the stock market closing price performance of the Colombo Stock Exchange (CSE) in Sri Lanka from 2000 to 2021. Multiple Linear Regression (MLR) and Long Short-Term Memory (LSTM) neural networks were used for this purpose. Predictor variables included the stock market’s open, high, and low prices and volume of shares, whereas the closing stock price was considered the response variable. A binary variable named “election influence” was also introduced as a predictor variable under seven sensitivity intervals before and after 1⁄2, 1, 2, 3, 4, 5 and 6 months from the respective election’s date. After being tested for multicollinearity, high price and election influence were considered in all the models’ deployments. The accuracy of MLR and LSTM networks was evaluated with and without election influence using mean absolute percentage error (MAPE). Ten national (presidential = 4 and parliamentary = 6) elections and five provincial council elections were considered. MLR and LSTM showed the highest accuracy levels of 97.01% and 87.32% for two months post and prior to the national election compared to MLR and LSTM without election (96.98%, 86.66%). However, the highest accuracy for 1⁄2 months before and after the provincial council election was observed in MLR (97.00%) and LSTM (87.09%) compared to MLR (96.98%) and LSTM (86.66%) without election influence. In conclusion, 2 and 1⁄2 months before and after the national and provincial council elections, the election influence could be a statistically significant predictor of closing stock prices in Sri Lanka under both MLR and LSTM. This research would emphasize the significance of election aspects in future predictions.
Comparison of radial basis function global method and radial basis function-finite difference (local) method as an interpolation technique
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Karunarathna, W.H.D.T.; Dissanayake, K.M.N.; Dewasurendra, M.T.M.
The Radial Basis Function (RBF) method is a numerical method that can be used to solve interpolation problems and partial differential equations (PDEs). There are two main types of RBFs: infinitely smooth RBFs and piecewise-smooth RBFs. Gaussian, Multiquadric, Inverse Multiquadric, and Inverse Quadric functions are examples of infinitely smooth RBFs commonly used with the global RBF approach. An important factor of the infinitely smooth RBFs is that they contain a shape parameter. When using the global RBF method, one has to choose a suitable value for the shape parameter as it dramatically impacts convergence. In addition, using the global RBF method is computationally expensive as it produces dense matrices. Therefore, the possibility of using the local RBF approach, known as the RBF-FD approach, is studied, along with shape parameter independent Polyharmonic Spline RBFs, to overcome the aforementioned obstacles. In order to create RBF-FD interpolation stencils, Polyharmoic Spline stencils augmented with polynomials were used. This is a common approach used to solve PDEs, which we adapt to solve interpolation problems. In this work, we interpolated 𝑓(𝑥, 𝑦) = 𝑥𝑒 ⁻ˣ²⁻ʸ² with various known nodes and fixed 6400 unknown 2D nodes on [-1, 1] by using Gaussian, Multiquadric and Polyharmonic Spline RBFs. Also, we calculated the error of the approximation for different known numbers of 2D nodes. The accuracy of the solution oscillated with the shape parameter. However, when we used the RBF-FD method, we observed a clear pattern of error decay when increasing the number of nodes. The order of convergence was in the realm of at least 𝑂(ℎ ᵖ ) to a maximum of 𝑂(ℎ ᵖ⁺² ) where ℎ is the fill distance and 𝑝 is the degree of the appended polynomial. In addition, unlike the global approach, the RBF-FD method produced sparse matrices, which leads to a computationally efficient and stable algorithm.
Stochastic flow model of groundwater in a small subsurface area in Sri Lanka
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Jayaratne, W.M.P.P.; Wijekoon, P.; Weerasooriya, R.
Porous medium and fractured hard rocks are the two main domains where groundwater can be found. As no randomness is involved, deterministic models can be utilized to represent the water flow in the porous medium. In contrast, quantifying groundwater movement through fractures is difficult due to its irregular distribution. In a heterogeneous environment, we estimate the aquifer parameter hydraulic conductivity, which has a complex spatial variation and high uncertainty. These circumstances are addressed by stochastic models. As the relevant published studies are not available in Sri Lanka, the objective of this study is to apply stochastic modelling to groundwater flow for a 20 km² area in Neetiyagama, Anuradhapura. This study specifically aims to quantify the spatial relationships of hydraulic conductivity between sample values using semi-variogram models, simulate the spatial distributions using Simulated Annealing and interpolate the values using Kriging interpolation. The dataset consists of hydraulic conductivities with location coordinates East and North of 41 samples. The semi-variogram is used to quantify the spatial relationship between the sample values. Semi-variance values were plotted with respect to lag distance. A Spherical model was chosen from semi-variogram models, and nugget, sill and range values were initialized based on the behaviour of semi-variance values. Simulated annealing is an application of the Monte Carlo method, which minimizes the squared difference between the desired and actual semi-variogram by generating realizations that are guaranteed to fit the actual semi-variogram. Using Simulated Annealing, the converged objective function, nugget, sill and range values were obtained, and the best fit for the Spherical model was identified. To approximate the values of unknown points in the study area, the known values of the measured data are interpolated using Kriging interpolation, and 253 realizations were yielded. Model validation was carried out by visualizing actual and predicted data, as there are few sample points in the model validation dataset. This can be further carried out with a proper validation dataset. The results of this study can be applied to geologically heterogeneous terrains and will be able to obtain a spatial distribution of hydraulic conductivity over the location coordinates.
An efficient homomorphic image encryption algorithm for cloud storage
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Malshika, N.N.D.; Wijesiri, G.S.
Today, an increasing amount of data is transmitted via the Internet. This data includes not only text but also audio, images, and other multimedia. Images are commonly used in our daily lives. However, it is vital to building a secure encryption scheme when delivering images over an unsecured network. Homomorphic cryptographic techniques protect privacy while allowing computation on encrypted data. Moreover, it is a type of encryption that allows users to compute encrypted content without decrypting it. Many public-key encryption techniques, including homomorphic encryption schemes, are theoretically proven but not deemed practical for various reasons, including the huge size of the public key. The study uses the Hermite Normal Form (HNF) encryption technique to provide an efficient homomorphic encryption algorithm for image processing operations on encrypted images saved in the cloud or transmitted over an unprotected connection. The HNF method has proven highly versatile and secure, making it ideal for homomorphic encryption. The scheme was tested using some generated codes in python language. Analyses like histograms and correlation are performed to verify the proposed scheme's efficiency. The experimental results demonstrate that the suggested strategy can accomplish efficiency and security for cloud users.
Prediction of tidal elevation along eastern and western coastal areas in Sri Lanka
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Perera, J.A.R.M.; Appuhamy, P.A.D.A.N.; Ekanayake, E.M.P.
Tidal height data provide vital information for the construction of ports, coastal buildings, development of the fisheries industry, and human activities. The conventional harmonic approach needs a significant volume of measurements to produce accurate predictions of tidal elevations. In order to overcome the difficulty in getting large volumes of data for conventional harmonic analysis, this research presents an Artificial Neural Network Technique called back-propagation procedure with a Stochastic Gradient Descent algorithm on limited data to forecast the tidal elevations in eastern and western coastal areas of Sri Lanka. Hourly tidal heights at Colombo and Trincomalee spanning from September 2020 to January 2021 were used for this study. The sine and cosine values of frequencies of significant tidal constituents at a particular hour were used as input neurons. Then the network structures were trained, validated, and tested for eight different periods viz., 7, 10, 15 days, and 1, 2, 3, 4 and 5 months, with zero and one hidden layer up to 10 neurons to find the minimum data required for accurate predictions. Using the Mean Squared Error (MSE) and the coefficient of determination (R²) to measure the accuracy of predictions, it was found that tides in Colombo are dominated by the mixed semidiurnal type, which is in contrast to the semidiurnal type observed in Trincomalee and in equatorial countries. Moreover, there was a substantial difference in mean tidal elevations at both locations. Out of 69 constituents, five were identified as significant with two months of hourly tidal measurements, which were the same for both locations. This corresponds to about 15% of data generally required for conventional harmonic analysis to identify the significant constituents. The optimal neural network structures for Trincomalee and Colombo areas were attained from fifteen days of data with 8 neurons and two months of data with 5 neurons, respectively, in the hidden layer, each of which yielded the minimum MSE and the highest R² value and thus efficiently predicting hourly tidal heights at each location.
Solving trapezoidal fuzzy transportation problems using geometric mean
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Sara, S.F.; Ekanayaka, E.M.U.S.B.
Optimization techniques are important in tackling real-world problems such as project timelines, assignment challenges, and network traffic analyses. As a result, this work focuses on the concept of fuzzy theory as it relates to transportation optimization. The application of fuzzy transportation problems has proven to be beneficial in the decision-making process. The proposed method utilizing the geometric mean technique to solve the fuzzy transportation problem has all the fuzzy demand and supply represented by trapezoidal fuzzy numbers. As a result, decision-makers will find this technique very simple to comprehend and apply to real-life transportation problems. In this work, instead of standard methods which are prevailing already, the geometric mean approach indices are used to convert the trapezoidal fuzzy transportation problem into a crisp transportation problem. A numerical case is solved to define the suggested method, and the result is compared with other well-known meta-heuristic methods. This approach is an easy and fast method to find solutions close to the optimal solution or near-optimal solution. Other types of issues, such as assignment issues, network flow issues, and project schedules, can also be resolved using this method.
Spatial and temporal variation of tree biomass in tropical rainforest of southwest Sri Lanka
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Herath, H.M.S.I.; Wijekoon, P.; Ediriweera, E.P.S.K.
Although tropical rain forests hold large amounts of carbon, there is uncertainty about the quantity and distribution stored in forests. The Above Ground Biomass (AGB) of forests provides estimates of the carbon pools, as 50% of AGB is carbon. Hence, the availability of reliable AGB estimates is important. This study was carried out in the 25-ha Sinharaja Forest Dynamic plot (FDP). This study aims to estimate the AGB in the FDP and analyze the spatial and temporal variation of the AGB of the FDP over 25 years. The stems of the selected species were analyzed at eight different diameter classes. The 20 most dominant species in the FDP were selected for analysis based on the Important Value Index (IVI). The estimated AGB of the selected species were analyzed at eight different diameter classes. The ANOVA repeated ANOVA and Kruskal-Wallis test were used to understand the significance of temporal variation and the variation of AGB across diameter classes. The total AGB in each quadrat was obtained in Mg ha⁻¹ and they were analyzed and visualized through spatial maps at a scale of 0.04 ha to understand the spatial variation of AGB. Further, AGB gains and losses over the years were calculated. Even though a change in AGB was observed over the years, the temporal variation of the overall AGB was not significant. However, the AGB change at diameter classes was highly significant. The spatial variability within the plot was high, and the spatial variation at 0.04 ha level over the years was statistically significant (p < 0.05). Most of the quadrats (80%) had AGB < 60 Mg ha⁻¹, and around 42% of quadrats contained AGB < 20 Mg ha⁻¹. The overall distribution of AGB in the FDP was positively skewed. Further, the total AGB in the FDP has decreased with time, indicating its role as a carbon source rather than a carbon sink.
Synchronization of multi-manufacturer multi-buyer integrated inventory supply chain model
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Hisam, M.S.M.; Juman, Z.A.M.S.; Daundasekera, W.B.
The manufacturer–buyer integrated inventory supply chain system is common practice and evolving into a significant factor in the more highly competitive environment encountered in today's global economy. Coordination between the manufacturer and the buyer offers benefits economically for both parties. Notable attention has been given to single-manufacture, single-buyer and single-manufacture multi-buyer integrated inventory systems with consideration of various realistic factors in the literature. This study was motivated by a real-world problem where six tea manufacturing factories produce a brand of tea and distribute their two buyers. However, to the best of our knowledge, only a few studies investigated multimanufacturer multi-buyer integrated inventory systems in previous research. Further, we assumed manufacturers transfer the lot just after its production and buyers have limited storage capacity to accommodate the required inventory. So, we first develop a multi-manufacturer multi-buyer integrated inventory model by accounting for realistic factors such as capacity limitation of buyer storage. In our study, manufacturers produce a homogenous product and supply it to all buyers to satisfy their demands. Besides, we consider unequal batch size transferring policy and assume the batch sizes follow geometric series. Then, we derive an optimal solution technique for the model to obtain the minimum total cost. Further, a sensitivity analysis is performed, and real-world tea distribution data is solved to support the analytical findings.
Based on modified ant colony algorithm for researching the minimum weight spanning tree
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Niluminda, K.P.O.; Ekanayake, E.M.U.S.B.
A Minimum Weight Spanning Tree (MWST) is a mathematical technique for connecting a set of points with the least amount of connecting lines. The MWST problem is among the most fundamental and intensely studied problems in network optimization, with a wide range of theoretical and practical applications. A common and well-known problem in combinatorial optimization is the MWST problem. The MWST visits all vertices in the same related portion as the starting node. In this study, several strategies are considered to solve the generalized MWST problem, and a novel approach is used to solve the MWST. MWST can be obtained using the well-known Prim and Kruskal algorithms. These algorithms can be divided into two groups according to the implementation. MWST is divided into two types: line-based MWST and node-based MWST. Prim's algorithm is node-based, whereas Kruskal's is a line-based algorithm. However, in this paper, we present a method for solving the MWST problem using a Modified Ant Colony Optimization (MACO) algorithm. Ant Colony Optimization (ACO) is a probabilistic method and a type of metaheuristic that has gained widespread use for solving combinatorial optimization problems, as well as a technique for determining the shortest path between two points. It is based on how ants behave as they travel from their nest (colony) to a food source in search of food. The algorithm has been improved in this unique way by modifying the ACO algorithm and including the transition rule and pheromone update rule. A comparable result can be obtained by applying Prim's and Kruskal's algorithms.
Open vehicle routing problem with moving shipments at the cross-docking terminal
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Gnanapragasam, S. R.; Daundasekera, W.B.
Vehicle Routing Problem (VRP) plays a vital role in supply chain (SC) management. The cross-docking (CD) strategy was introduced in the 1930s to reduce up to 70% of warehousing at traditional distribution centres in SCs. The research on integrating VRP with CD (VRPCD) was initiated in 2006. Open VRP (OVRP) is one of the variants of VRP, and it is more suitable for organizations which outsource the fleets of vehicles from third-party logistics (3PL) companies. In this study, one of the internal operations at the CD terminal (CDT), moving shipments (MS) from receiving doors to the shipping doors of CDT, is integrated with VRPCD. Consequently, this study considers open VRPCD with MS at CDT (OVRPCDMS). As an additional feature in this study, two sets of fleets of vehicles with two different capacities are added for pickup and delivery processes separately. Furthermore, the service cost at each customer and at receiving and shipping doors of CDT is considered when calculating the total cost of transportation. Moreover, the asymmetric distance between any two customers is assigned by incorporating a characteristic of one-way routes between cities in real-life transportation. The objective of this study is to minimize the total transportation cost which incurs travelling costs between customers, service cost at customer points, service cost at the receiving and shipping doors of CDT, cost of moving shipments inside the CDT and finally, the cost of hiring fleets of vehicles from 3PL. To solve the OVRPCD-MS problem, a mixed integer linear programming (MILP) model is developed. The programming models was implemented in LINGO (version 18) optimization software. The branch and Bound algorithm is employed to solve ten small-scale instances generated randomly. The applicability of the proposed MILP model is observed. The required fleets of vehicles to be hired and the run time to reach the optimal solution is determined. The study revealed that the average run time is exponential for small-scale instances. Thus, it can be concluded that this proposed model can be used for the last time in the planning of similar, small-size instances. At the same time, the combinatorial nature of VRP makes OVRPCD-MS as NP-hard problem. Therefore, this study recommends that heuristic or metaheuristic methods are more appropriate for the medium and large-scale instances of OVRPCD-MS to reach near-optimum solutions. This further recommends incorporating additional constraints to the OVRPCD-MS model, such as time windows for each customer, budget allocations for fleets of vehicles and temporary storage capacity at CDT to cover a broader spectrum of a study under investigation.
Skew-t replicated measurement error model for method comparison data
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Duwarahan, J.; Nawarathna, L.S.
Method comparison studies are designed to determine whether the two methods of quantifying a continuous variable are compatible enough to be used interchangeably. The linear mixed-effects model is often used to model method comparison data when the methods have the same measurement scale. During the data collection, Measurement Errors (MEs) will occur in observations of covariates and response variables, and these mistakes may be caused by using different measuring scales or methods. If these MEs are not considered, the conclusion will be misleading. This study discusses the framework for modelling method comparison data for quantitative measurements with the MEs, called the 'Measurement Error Model' (MEM). These models generally assume normality for true covariates and errors. However, these assumptions are frequently violated in practice due to the skewness and heavy tails. The key objective of this research is to develop a Skew-t Replicated Measurement Error Model (ST-RMEM) under skew-t distribution for true covariate and t distribution for errors with a matching degree for analyzing the degree of similarity and agreement between the two methods. Further, the Skew-Normal RMEM (SN-RMEM) and Normal RMEM (N-RMEM) models were considered for comparative purposes. The expectation- maximization (EM) approach was used to fit the model. The simulation research was carried out to validate the proposed methodology using sample bias (BIAS), standard deviation (SD), root mean square error (RMSE), and coverage probability (CP) measures. These values under ST-RMEM were better than the N- RMEM and SN-RMEM in all cases. Moreover, this methodology is demonstrated by analyzing subcutaneous fat data. In addition, the Total Deviation Index (TDI) and Concordance Correlation Coefficient (CCC) were utilized to assess method agreement. The CCC estimate for ST-RMEM is 0.990, with a lower bound of 0.984, while the TDI estimate for ST-RMEM is 0.034, with an upper bound of 0.050, suggesting good agreement amongst the methods. These results indicate that our suggested model works well for analyzing replicated method comparison data with measurement errors, skewness, and heavy tails, which are frequent in many fields such as medical research, epidemiological studies, economics, and the environment.
Responses for paleocene-eocene thermal maximum: evidenced by calcareous nannofossil assemblages of the Mannar basin, offshore Sri Lanka
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Wijesinghe, W.M.H.M.; Wijenayake, A.U.; Dharmapriya, P.L.; Gyawali, B.R.; Malaviarachchi, S.P.K.; Kularathna, E.K.C.W.
The Paleocene-Eocene transition, spanning about ~170 to ~217 kyr, records a significant and extreme global warming event known as Paleocene-Eocene Thermal Maximum (PETM). PETM is marked by temperature elevations across ocean water columns and lateral temperature increments in the tropics to high latitude regions. The effects of these climatic events have been discussed by many researchers as a bloom of many biotic assemblages. In this research segment, we focused on identifying the paleoclimatic changes associated with the Mannar Basin during the period of PETM by using calcareous nannofossil assemblage. The samples were deep-marine carbonate-rich sediments selected within the depth of 2,400 – 2,605 m at 25 m intervals from the Dorado-North Hydrocarbon Exploration well drilled in the Mannar Basin, Sri Lanka. Simple smear slides were prepared and observed under the polarized microscope with an oil-immersion objective lens (magnification 1000x). Based on the calcareous nannofossil stratigraphy, the age determined for the section is Late Paleocene to Early Eocene (P/E), which traverses from biozone NP8 to zone NP10 and the subzones of NP9; NP9a and NP9b were identified. Calcareous nannofossils discovered at the P/E boundary are distinguished by a considerable rise in warm water taxa (e.g., Sphenulithus, Discoaster, Ericsonia, Fasiculithus). The pre-PETM and post-PETM periods were characterized by the presence of cold-water taxa (Coccolithus, Toweius and Chiasmolithus). The study samples showed evidence for an increasing temperature of the ocean surface, with an increase in the relative abundance of dissolution-resistant forms (D. multiradiatus and F. tympaniformis) and the decrease in the relative abundance of cold-water taxa (C. pelagicus and T. pertusus) during the PETM, while ceasing of the event could be inferred by the increasing of cold-water species (e.g., Coccolithus, Toweius and Chiasmolithus) upon reaching the Early Eocene.
Distribution and abundance of common coot (fulica atra) and common moorhen (gallinula chloropus) in the Jaffna Peninsula, Sri Lanka
(Postgraduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka, 2022-10-28) Rajkumar, P.; Wijesundara, C.S.
The Common Coot (Fulica atra) is a less common breeding resident in the lowlands of the Northern part of Sri Lanka, while the Common Moorhen (Gallinula chloropus) is a locally rather common breeding resident in the lowlands throughout the country. The significant extents of mangroves, lagoons, and ponds in the Jaffna Peninsula provide ideal habitats for both these species. Their distribution and abundance have not been studied in the area, and this may hinder the conservation activities of these species. Hence, the objective of the present study was to determine the distribution and abundance of these species in the Jaffna Peninsula. Point counts are used in this study, which was undertaken from 2013 to 2018. To observe birds, binoculars (8×40 and 10×42) and a spotting scope (25×50) were used. Peak observation hours were between 0630-0830 h and 1530-1830 h, and counts of these birds were taken monthly. Each of the 12 sites was visited multiple times throughout the study period. The total number of individuals averaged 1,724 for the Common Coot and 116 for the Common Moorhen from the 12 sites during the study period. The main sites frequented by these birds included mangrove areas such as Sarasalai, Anthanathidal, Nagar Kovil, Kudarappu and Mamunai-Chempiyanpattu, and paddy areas associated with ponds such as Nunavil, Maravanpulavu, and major ponds in the Jaffna town. The highest number of common coots (532) was recorded from the Anthanathidal area. These two species have also been recorded in the Island areas of Jaffna. The study showed that both are rare resident birds in the Jaffna Peninsula compared to other waterbird species. However, the Jaffna breeding population of both species does not currently appear to be exposed to any serious threats. The wetland areas of the Jaffna Peninsula are potentially good birding destinations, which provide opportunities for ecotourists to enjoy many rare resident species like these. Hence, more attention should be given to the conservation and ecology of such species.

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