MERCon - 2020

Permanent URI for this collectionhttp://192.248.9.226/handle/123/16315

Browse

Now showing 1 - 20 of 113

item: Conference-Full-text
3d full-field deformation measuring technique using digital image correlation
(IEEE, 2020-07) Nadarajah, S; Arulkumar, V; Mallikarachchi, C; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
Full-field deformation measurements are crucial as it offers detailed information to better understand both micro and macroscopic nature of material behavior. The practice of employing Digital Image Correlation (DIC) based measuring techniques in experiments has increased due to its ability to generate full-field deformation information with minimal effort. Even though DIC systems are commercially available, the affordability of those systems is questionable in local context due to high capital costs. Most of the past studies related to DIC were focused on testing concrete, masonry and metallic alloy specimens, and little effort has been made on materials with recoverable large elongations. This paper presents a 3D fullfield deformation measuring system that has been developed with a special focus on hyperelastic materials. The proposed system requires two common digital cameras for image acquisition, as the depth information is of interest. Images are then processed using the MATLAB-based algorithm developed to produce the full-field deformation map. Hyperelastic specimens of two different thicknesses were tested over 70% strain and the accuracy of the strain measurement using the proposed system is validated against physical measurements. The results have shown that the strains can be captured to an accuracy greater than 90% using the proposed technique.
item: Conference-Full-text
Adaptive centroid placement based snic for superpixel segmentation
(IEEE, 2020) Senanayaka, JB; Morawaliyadda, DT; Senarath, ST; Godaliyadda, RI; Ekanayake, MP; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
The proposed image segmentation algorithm identifies information-rich versus low information regions based on surface entropy. Thereafter on the information-rich regions, the mean shift algorithm is applied to generate possible centroid initialization points. This enables the Simple Non-Iterative Clustering (SNIC) algorithm when initialized through the proposed mechanism to provide more concentrated segmentation in those information-rich regions and sparse segmentation in the low information regions.
item: Conference-Full-text
Analysis of bulking factor as a basis for royalty calculation in aggregate quarrying in Sri Lanka
(IEEE, 2020-07) Perera, T; Piyarathna, S; Liyanage, I; Panagoda, H; Dharmaratne, P; Samarasuriya, C; Samaradivakara, I; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
Sri Lanka hosts a variety of mineral resources and the government grants necessary approvals required for mining. As compensation Government charges a royalty. Currently, in aggregate production in Sri Lanka, an explosivebased equation is used for royalty levy calculation which has not been scientifically established where bulking of the material is not considered. As mineral royalty levy is one of the main revenues of the state, deviations of royalty recovery will influence the economy of the country. The study is being conducted on several A grade quarries, and Total Station surveys were used to obtain 3-dimensional coordinates of the muck pile before and after blasting. These data were used to generate a 3D model of the muck pile and the bench, which was used for the bulk volume calculations with the use of the Surfer 16 software. The in-situ volume of the blasted rock was found by truck weight calculations and both the bulk volume and the In-situ volume were used for Bulking Factor calculations, and Powder Factor calculations. This research will lead to significant alterations in the royalty calculations. This approach with new technology will put the royalty calculation on a scientific putting and elevate the royalty calculation methodology.
item: Conference-Full-text
Analyze the potential of developing port of Colombo as a cruise hub in South East Asia
(IEEE, 2020-07) Amarathunga, O; Sigera, I; Edussooriya, C; Weeraddana, CUS; Abeysooriya, RP
This research paper describes a comprehensive study done to identify the cruise port infrastructures and port side supply for improved cruise operation in the port of Colombo, in order to capture the future potential to develop as a cruise hub in south-east Asia. Similarly, it assesses the current situation of the port of Colombo and identifies the global best practices and strategies to identify what are the cruise market demand factors and supply-side capabilities. Based on the objectives of the study, 47 required cruise port evaluation criteria and global strategies were identified by observing previous studies and literature reviews. Under the evaluation of opinions of industry experts, Factor rating was used as primary data analysis tools, to filter out the most significant factors. Main factors, which contributed to cruise port development are port infrastructure, cruise shipping policies, services for cruise passengers and political and regulatory framework.
item: Conference-Full-text
Analyzing the geographical catchment areas of fort-malabe lrt by access modes
(IEEE, 2020-07) Mendis, BHA; De Silva, GLDI; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
Development of transport sector is a timely need for a developing country such as Sri Lanka. Especially the public transport sector. Mass transit systems serve as the backbone transport systems while feeder modes enable the connections between the origins and mass transit connection points. Currently passengers use private feeders and non-private modes. A proper feeder network is vital for the success of a mass transit network. In this paper, Fort- Malabe LRT which is the newest mass transit that is being introduced to Sri Lanka, is analyzed. Spatial extents of catchment areas for access modes were taken using survey data for each feeder mode. The station wise catchment distances and corridor wise catchment distance for each mode is discussed and compared. There are two approaches utilized in identifying the geographical buffer area. In the first approach, circular buffer, the area that is contained by the Euclidean catchment distance is taken. In service area approach the catchment by road network is taken. The geographical catchment areas for different access modes were concluded, for each mode of feeder, using Geographical Information Systems (GIS) and solutions that can be applied for maximizing the catchment areas were suggested using Conveyal analysis.
item: Conference-Full-text
An approach to identify bottlenecks in road networks using travel time variations: a case study in the city of Colombo and suburbs
(IEEE, 2020-07) Thilakshan, T; Rajapaksha, G; Bandara, S; Edussooriya, C; Weeraddana, CUS; Abeysooriya, RP
Bottlenecks in road networks are the main contributing factor in terms of traffic congestion in urban areas and thus, identification of bottlenecks and introduction of relevant remedies are important in easing the traffic congestion especially in the case of developing countries where funding for new transport infrastructure projects is a major factor of concern. This study discusses on identification of bottlenecks using crowdsource real- time travel time data which is more effective in terms of collection and usage in analysis. The usual travel time collection process is thus replaced by using Google Maps API matrix. Shortest travel time and travel distance paths among main origin and destinations are analyzed and the contrast in shortest distance path not being the shortest travel time path brings an important consideration of the reasons associated mainly due to presence of bottlenecks which needs to be identified and rectified for better road user experience. After a macro level approach in the identification process, certain transportation indices such as Congestion Index, Delay Rate Index and Travel Rate Ratio in a meso and micro level analysis perspective are utilized to ensure the identification of critical bottlenecks along minimum distance paths in the road network of main roads.
item: Conference-Full-text
Assessment of the potential of co2 sequestration from cement flue gas using locally isolated microalgae
(IEEE, 2020-07) Wijayasekera, SCN; Cooray, BY; Premaratne, M; Ariyadasa, TU; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
Carbon dioxide (CO2) emissions are rapidly escalating due to industrialization and urbanization worldwide, resulting in many long-term adverse effects such as global warming. Industrial flue gases which contain 3-30% CO2 (v/v) are a major constituent of global CO2 emissions. Employing microalgae for biological fixation of CO2 from flue gas is a prospective strategy for the reduction of CO2 emissions since microalgae have the capability of utilizing inorganic carbon to rapidly generate biomass via photosynthesis. In the current study, the locally isolated microalgal strains Chlorella sp. and Desmodesmus sp. were employed to assess the CO2 sequestration potential from simulated flue gas, comparable to the emissions from the cement industry. The gross calorific values (GCVs) were determined to evaluate the potential of employing microalgal biomass for co-firing processes. Desmodesmus sp. showed the highest CO2 tolerance, as it exhibited a biomass productivity and CO2 fixation rate of 1.17 g L-1 and 0.26 g L-1 day-1 respectively under undiluted flue gas (15.50% CO2). However, the GCVs of Chlorella sp. biomass were higher than Desmodesmus sp. biomass under all flue gas dilutions. Nonetheless, the GCVs of Desmodesmus sp. were in the range of 23.277-24.202 MJ/kg, comparable to biomass typically used in co-firing applications.
item: Conference-Full-text
Automated vehicle parking occupancy detection in real-time
(IEEE, 2020-07) Padmasiri, H; Madurawe, R; Abeysinghe, C; Meedeniya, D; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
Parking occupancy detection systems help to identify the available parking spaces and direct vehicles efficiently to unoccupied lots by reducing time and energy. This paper presents an approach for the design and development of an end-to-end automated vehicle parking occupancy detection system. The novelty of this study lies in the methodology followed for the object detection process using RetinaNet one stage detector and region-based convolutional neural network deep learning technique. The proposed software architecture consists of low coupled components that support scalability and reliability. The developed web-based and mobile-based client applications assist to find parking spaces easily and efficiently. The existing solutions utilize dedicated sensors and depend on manual segmentation of surveillance footage to detect the state of parking spaces. The proposed approach eliminates existing limitations while maintaining reasonable accuracy.
item: Conference-Full-text
Biodegradable Composite for Temporary Partitioning Materials
(IEEE, 2020-07) Dassanayaka, D; Hedigalla, D; Gunasekera, U; Edussooriya, C; Weeraddana, CUS; Abeysooriya, RP
Building construction can be considered as one of the indispensable industries in the world. Even though the necessity of the industry is evident, its current practices are not environmentally friendly. Some of the main reasons for this is the usage of unsustainable raw materials such as sand and soil, as well as the usage of harmful non-biodegradable materials such as PVC, asbestos. When considering the applications of raw materials used in the construction industry, nearly 40% of them are used for manufacturing non-load bearing constructions such as partitioning materials. In this research, a method for manufacturing a novel biodegradable movable partitioning material has been discussed. This partitioning material is a composite, created with banana yarn as reinforcement, Poly-lactic acid as the matrix, manufactured using compression moulding technique. Furthermore, two different types of composites were manufactured by changing the yarn laying directions, which are unidirectional and bidirectional. Flexural and impact strength of both types of composites have been tested by varying the weight percentage, the pretension of yarns and processing parameters: moulding temperature and moulding pressure. Finally, several weight percentages, pre-tensioning values, moulding temperatures and moulding pressure values have been suggested in order to manufacture a quality partitioning material.
item: Conference-Full-text
Blockchain-based product traceability beyond proof of existence
(IEEE, 2020-07) Perera, T; Hettige, SPT; Jayatilake, SAP; Abeygunawardhana, W; Bandara, HMND; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
Contemporary consumers are demanding greater visibility in products they consume, and practices used to pro-duce them. Blockchain-based product traceability solutions at-tempt to integrate the data silos of suppliers into an immutable and distributed ledger to provide consumers with a transparent and trustworthy system to trace back a product at hand. A com-mon limitation of these solutions is the use of blockchain to pro-vide only the proof of existence of data. We propose a solution where data related to enforcement of product-quality specifica-tions and production limits, merging and splitting products as batches, and mixing of ingredients are handled within the block-chain itself to provide greater consistency, transparency, and trust. Our solution is based on a graph data structure built into the blockchain nodes, smart contracts, and facilitation of differ-ent roles in a supply chain. We demonstrate the utility of the proposed solution by implementing it on the Hyperledger Fabric platform. Performance results confirmed that both the graph data structure and blockchain has acceptable throughput and latency characteristics.
item: Conference-Full-text
Bond-slip models of cfrp/steel double strap joints subjected to long term exposure of moisture and elevated temperature
(IEEE, 2020-07) Perera, UND; Chandrathilake, ERK; Gamage, JCPH; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
Strengthening of deteriorated steel elements using Carbon Fiber Reinforced Polymer (CFRP) materials is widely gaining appeal. Since the majority of applications can be seen in outdoor structures, the evaluation of long-term behaviour under various environmental conditions is an important aspect. In the present study, the bond performance of CFRP strengthened steel double strap joints immersed in distilled water at ambient (28 oC) and elevated (40 oC) temperatures for six months was examined. A total of twelve specimens were tested including four control specimens and eight number of conditioned specimens. A numerical model was also developed. The model results are in good agreement with experimental results. The bond shear stress – local slip curves were then developed for each environmental condition using model predicted strain readings. The bond-slip models showed a bond shear strength degradation of about 24 % at 28 oC and 30 % at 40 oC within the exposure duration of six months.
item: Conference-Full-text
Bridge ontology architecture for knowledge management in bridge maintenance
(IEEE, 2020-07) Banujan, K; Vasanthapriyan, S; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
The construction sector depends on a broad variety of information from very different sources. Especially when constructing bridges, huge experience, and extensive knowledge is important. Knowledge Management (KM) is the key to share explicit and tacit knowledge in the bridge construction. As an initiation for the KM, an ontology for bridge maintenance was developed. As the first step bridge maintenance related data were collected. Then taxonomy was developed. As a next step, the bridge maintenance ontology was developed using Protégé OWL Ontology Editor. Finally, the modeled ontology was evaluated using tools and ontology experts. We strongly believe that our novel approach to bridge maintenance ontology can support all the actors on the construction site and as well as students and researchers.
item: Conference-Full-text
Chemical modification of microcrystalline cellulose using sunflower oil
(IEEE, 2020-07) Rathnayake, WSM; Karunanayake, L; Samarasekara, AMPB; Amarasinghe, DAS; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
Structural, thermal, physical and mechanical properties of microcrystalline cellulose (MCC) combined with its biodegradability make an excellent platform for the aptness of MCC in reinforcing polymeric composites along with a commercial success in the context of green chemistry. Main drawback of above union is the incompatibility of hydrophilic MCC and hydrophobic polymers which ultimately damp the desired property improvements. With a prospective and pioneering a green approach, this study introduces a novel method to modify the surface of MCC to introduce surface hydrophobicity. State of the treatment was analyzed with acyl percentage, FTIR analysis, wettability test, SEM images and TGA thermographs. Results uphold the success of the transesterification reaction of sunflower oil ethyl esters (SFEEs) with MCC showing higher attraction to nonpolar dichloromethane with an improved thermal stability. FTIR showed the successfully grafted SFEEs onto MCC surface. Modified MCC can be used in the fabrication of polymeric substances in the process of improving its mechanical properties simultaneously under green chemistrybased approach.
item: Conference-Full-text
Chronic Kidney Disease Prediction Using Machine Learning Methods
(IEEE, 2020-07) Ekanayake, IU; Herath, D; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
Chronic Kidney Disease (CKD) or chronic renal disease has become a major issue with a steady growth rate. A person can only survive without kidneys for an average time of 18 days, which makes a huge demand for a kidney transplant and Dialysis. It is important to have effective methods for early prediction of CKD. Machine learning methods are effective in CKD prediction. This work proposes a workflow to predict CKD status based on clinical data, incorporating data prepossessing, a missing value handling method with collaborative filtering and attributes selection. Out of the 11 machine learning methods considered, the extra tree classifier and random forest classifier are shown to result in the highest accuracy and minimal bias to the attributes. The research also considers the practical aspects of data collection and highlights the importance of incorporating domain knowledge when using machine learning for CKD status prediction.
item: Conference-Full-text
Classification of cyberbullying Sinhala language comments on social media
(IEEE, 2020-07) Amali, HMAI; Jayalal, S; Jayalal, S; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
Due to technological revolution over the years, bullying which was confined to physical boundaries has now moved online. Denigration or insult is one form of cyberbullying. According to Sri Lanka Computer Emergency Readiness Team, social media cyberbullying incidents are escalating. Insulting words are dynamic, and same word can have several meanings according to the context. Simply because a comment contains such a word, it cannot be classified as bullying. Hence, when labeling comments, simple keyword spotting techniques are inadequate. Other languages have addressed this issue using lexical databases such as WordNet which provides synonyms and homonyms of words. Since there is no proper lexical database developed for Sinhala language, detecting a word as bullying is a challenge. Therefore, we used rules to overcome this issue. Twitter comments with profane words were collected, outliers were removed, and remaining tweets were pre-processed. To determine insult in the text, five rules were used for feature extraction. Afterward, we applied Support Vector Machine (SVM), K-nearest neighbor (KNN) and Naïve Bayes algorithms. The results show that SVM with an RBF kernel performs better with an F1-score of 91%. Novelty of this research is the focus on Sinhala language cyberbully detection which has not been addressed before.
item: Conference-Full-text
Control Channel Denial-of-Service Attack in SDN-Based Networks
(IEEE, 2020-07) Sriskandarajah, S; McKague, M; Foo, E; Ragel, RG; Karunarathna, SN; Jadidi, Z; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
Software-Defined Networking (SDN) is an architectural approach that fulfils the requirement of high bandwidth and the dynamic nature of current applications. One of the key features of the SDN architecture is the separation of the control logic from data plane devices. This key feature introduces a new type of control traffic in the SDN architecture, which opens the space for new vulnerabilities to SDN-based networks. In this paper, we first present an attack model to exploit the control channel of the SDN architecture. We then experimentally evaluate the impact of the attack on the end-users of the SDNbased network using our physical experimental testbed. Our experimental results clearly show that the control channel DoS attack has a major impact on the end-users of the SDN-based networks.
item: Conference-Full-text
A data driven binning method to recover more nucleotide sequences of species in a metagenome
(IEEE, 2020-07) Vimukthi, K; Wimalasiri, G; Bandara, P; Herath, D; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
Metagenomics accelerated the process of studying different species and their dynamics in multiple environments. A key step in a metagenomic study is to group nucleotide sequences belonging to an individual or closely related species which is often termed binning. Multiple machine learning techniques have been adopted in binning metagenomic sequences. Specifically, unsupervised learning is being used in most of the recent binning methods. This work considers data-driven methods for binning metagenomic sequences and discusses such approaches in detail. Furthermore, it explores on increasing the amount of metagenomic sequences binned while maintaining a reasonable binning accuracy. Consequently, a dissimilarity-based approach is proposed to improve the number of contigs binned by an existing binning method. It is shown to result in a 10% increase in the number of contigs binned compared to the original approach. Accordingly, this work suggests that the effective use of observed data which may be discarded as outliers otherwise, may result in improved performance in binning.
item: Conference-Full-text
Design and analysis of a mems based transdermal drug delivery system
(IEEE, 2020-07) Perera, KNM; Awantha, WVI; Wanasinghe, AT; Herath, HMDP; Paththinige, SSHG; Ekanayaka, L; Amarasinghe, YWR; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
The design and analysis of a Micro Electromechanical System-based (MEMS-based) Transdermal Drug Delivery System are presented in the research article. A conceptual design for the delivery of Levodopa was proposed by the authors. Major components of the system were identified as a microfluidic pump, microneedle array and the microfluidic channels connecting the system. The working principles of these components were selected according to the persisting requirements and design considerations. Simulations were conducted to evaluate the performance and to optimize the design of the system. A fabrication method for the system was proposed by the authors as a stacked layer. The results of the simulations conducted were presented. The simulations show positive results with the performance of the system and do not suggest a mode of mechanical failure of the system at the given boundary conditions. The paper concludes with recommendations for future work.
item: Conference-Full-text
Design of a sustainable automotive turbocharger remanufacturing system
(IEEE, 2020-07) Jayawardane, H; Wijesinghe, K; Wildeniya, P; Gamage, JR; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
Remanufacturing has been identified as the process of returning of end-of-life products to original or better condition and performance with lower resource consumption, waste, and emissions compared to conventional manufacturing. Remanufacturing aids to reduce the economic, environmental, and social impacts of manufacturing. The purpose of this study is to investigate several product recovery cases performed at different levels to identify opportunities for developing remanufacturing systems in the Sri Lankan context. A literature review, semi-structured interviews, and case study visits were conducted for data collection. The analysis shows that the automotive sector in Sri Lanka is the most suitable sector to introduce remanufacturing, within which turbocharger has been identified as the most suitable component for remanufacturing. A model for the turbocharger remanufacturing system is proposed, and the sensitivity of the system to different operating scenarios is also analysed using plant simulations. The paper presents an economically viable and environmentally benign remanufacturing system with a business plan, which can be implemented in Sri Lanka.
item:
Design, fabrication and testing of lead zirconate titanate based ultrasonic wave generator
(IEEE, 2020-07) Selvarathinam, S; Adikary, U; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
In this research, a low cost piezoelectric ultrasonic wave generator was developed using mathematical calculation and finite element analysis. Then a prototype was fabricated to compare the performance. Resonance frequency, dimensions of design and acoustic impedance of matching layer and backing layer were determined by mathematical calculation. To optimize the parameters of the design, finite element analysis was used. The layer parameters were calculated using 3D model of Finite Element Analysis. Finally, transmitting wave frequencies in water and air were calculated from acoustic pressure variation, which derived as a result of simulation using 2D axisymmetric model. Arduino software was used to feed controlled electric signal to piezoelectric material. Based on Finite Element Analysis, the prototype device was fabricated using Lead Zirconate Titanate as the piezoelectric ceramic, Aluminum as the matching layer and Low Carbon Steel as the backing layer. Terminal wires were soldered and all three were merged together using glue gun with polymer based binders. Testing of the prototype was performed using the Oscilloscope. The resonance was observed at 75 kHz, 182 kHz, and 231 kHz. It was also confirmed by Impedance vs. Frequency analysis using Inductance Capacitance Resistance meter.

Browse

Browsing MERCon - 2020 by Conference "Moratuwa Engineering Research Conference 2020"