Browsing by Author "Edussooriya, CUS"

Now showing 1 - 20 of 103

item: Article-Full-text
A 3-D sparse FIR frustum filter for enhancing broadband plane waves
(IEEE, 2019) Wijesekara, RT; Edussooriya, CUS; Bruton, LT; Agathoklis, P
A 3-D FIR frustum filter having sparse coefficients is proposed for enhancing broadband plane waves received by uniform aperture arrays. Motivated by the design technique of 1-D interpolated FIR filters, the proposed filter is realized by cascading a spatially-upsampled 3-D FIR prototype filter having a frustum-shaped passband and a 3-D FIR masking filter having a parallelepiped passband. Sparsity of the filter coefficients is achieved through the spatial upsampling of the coefficients of the prototype filter and by hard-thresholding the coefficients of both prototype and masking filters. The proposed 3-D FIR frustum filter saves 39:5% multiplications and 66:6% additions compared to the state-of-the-art 3-D FIR frustum filters without degrading the performance in enhancing broadband plane waves.
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
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
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
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: Article-Full-text
Deep optical coding design in computational imaging
(2023-03-01) Arguello, H; Bacca, J; Kariyawasam, H; Vargas, E; Marquez, M; Hettiarachchi, R; Garcia, H; Herath, K; Haputhanthri, U; Ahluwalia, BS; So, P; Wadduwage, DN; Edussooriya, CUS
Computational optical imaging (COI) systems leverage optical coding elements (CEs) in their setups to encode a highdimensional scene in a single or in multiple snapshots and decode it by using computational algorithms. The performance of COI systems highly depends on the design of its main components: the CE pattern and the computational method used to perform a given task. Conventional approaches rely on random patterns or analytical designs to set distribution of the CE. However, the available data and algorithm capabilities of deep neural networks (DNNs) have opened a new horizon in CE data-driven designs that jointly consider the optical and computational decoders. Specifically, by modeling the COI measurements through a fully differentiable image-formation model that considers the physics-based propagation of light and its interaction with the CEs, the parameters that define the CE and the computational decoder can be optimized in an end-to-end (E2E) manner. Moreover, by optimizing just CEs in the same framework, inference tasks can be performed from pure optics. This work surveys the recent advances in CE data-driven design and provides guidelines on how to parameterize different optical elements to include them in the E2E framework. As the E2E framework can handle different inference applications by changing the loss function and the DNN, we present low-level tasks such as spectral imaging reconstruction or high-level tasks such as pose estimation with privacy preservation enhanced by using optimal task-based optical architectures. Finally, we illustrate classification and 3D object-recognition applications performed at the speed of the light using all-optics DNNs.
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.
item: Conference-Full-text
Designing a robust controller to damp sub-synchronous oscillations in power systems
(IEEE, 2020-07) Gamage, CM; Wadduwage, DP; Weeraddana; Edussooriya, CUS; Abeysooriya, RP
Series compensation using capacitor banks is a common technique used in power transmission systems, to improve the power transferring capability. However, it may lead to the generation of some natural frequencies due to the combination of inductor and capacitor. These frequencies are called as sub-synchronous frequencies which are below the power frequency of the power systems. They can give rise to sub-synchronous resonance (SSR). The SSR can cause physical damages to the power system equipment unless it is detected and mitigated prudently. This paper presents a robust controller which can be used to damp undesirable sub-synchronous oscillations. The small signal model required to design the controller is constructed using dynamic phasor approach. The performance of the controller is demonstrated using IEEE first benchmark model (FBM) for SSR studies. It’s shown that the proposed robust controller satisfactorily work under different operating conditions.