Browsing by Author "Bandara, HMND"

Now showing 1 - 20 of 105

item: Conference-Full-text
A 480mhz roach-2 fpga realization of 2-phase 2-d iir beam filters for digital rf apertures
(IEEE, 2016-04) Seneviratne, V; Madanayake, A; Bruton, LT; Jayasekara, AGBP; Bandara, HMND; Amarasinghe, YWR
RF antenna array beamforming based on electronically steerable wideband phased-array apertures find applications in communications, radar, imaging and microwave sensing. High-bandwidth requirements for wideband RF applications necessitate hundreds of MHz or GHz frame-rates for the digital array processor. A systolic architecture is proposed for the realtime implementation of the 2-D IIR beam filter. This implementation employs a differential-form polyphase 2-D IIR frequencyplanar beam filter, and a corresponding circuit architecture in order to achieve the real-time computation of the input-output 2-D difference equation that defines the RF beam filter. The feasibility of real-time implementation for dense aperture arrays operating in the 0-240 MHz band using a beam filter is explored. The proposed 2-phase sampling scheme per antenna is based on a 2-D IIR polyphase structure. A digital hardware prototype is designed, implemented and tested using a ROACH-2 fitted with a Xilinx Virtex-6 Sx475t FPGA chip and a 32-channel timeinterleaved RF data converter, which support 16 antennas using 2-phase time-interleaved sampling at an FPGA clock rate of 240 MHz.
item: Thesis-Abstract
Accelerated complex event processing with graphics processing units
Rodrigo, PS; Bandara, HMND; Perera, S
As Big Data scenarios increasingly become common, a large number of distributed data processing systems require timely processing of high volumes of real-time data streams. Detecting complex correlations between incoming data streams in near real-time is at the heart of these data processing systems. Complex Event Processing (CEP) have been dominating in this domain since inception a decade back. But, growth of Big Data volumes demands for more performance and faster processing. CEP operators like stream join and event patterns require considerable processing power and have huge impact on the overall query processing performance. In some use cases these operators have to operate on lots of events simultaneously. Making parallel algorithms for these operators is a common approach for improving the individual operator performance. A Graphics Processing Unit (GPU) provides a vast number of parallel computing cores and leverage new parallel algorithms which enables novel problem solving approaches for existing problems. But the challenge is combining complex event processing and GPUs in the right way to get the maximum performance out of the this parallel hardware. There had been attempts to use parallel hardware in improving CEP performance in both commercial and academic implementations, and most of them uses multi-core approach. Only a very few researches had used GPUs for CEP. We believe the lack of GPU related CEP researches is that they are not designed to bene t from parallel processing in GPUs. In this research we investigate how and when GPUs can be used to improve the query processing performance of a popular open source CEP implementation, Siddhi CEP. Siddhi, by design, supports for parallel query processing in multi-core CPUs. This work propose a novel approach for parallel event processing in GPUs with several GPU event processing algorithms. Performance evaluation on our implemented algorithms shows, for a mix of complex queries, parallel event processing on GPUs achieve more than ten times event processing throughput than the sequential processing in CPUs. Moreover, our approach helped to reduce event queuing at the incoming event queue when there are high frequent input event stream and several complex queries.
item: Conference-Abstract
Accelerating complex event processing through GPUs
Rodrigo, PS; Bandara, HMND; Perera, S
Complex Event Processing (CEP) is a well-known technology in real-time Big Data processing systems. Performance of CEP engines is expected to scale with ever-increasing data rates and complex use cases. CEP operators like stream join and event patterns involve high computational complexity; hence, have a considerable impact on the overall query processing performance. Distributed event processing and CPU-level parallel event processing algorithms are common approaches for improving the performance. We explore how commodity massively parallel architectures like modern Graphics Processing Units (GPUs) can be utilized to improve the performance of frequently used CEP operators. We demonstrate how CEP operators such as event filter, event window, and stream join can be redesigned and implemented on GPUs to gain an order of magnitude improvement in throughput compared to a CPU-based mplementation. This work is demonstrated using NVIDIA CUDA based implementation of CEP operators for Siddhi CEP engine on low-end GPUs. Moreover, this approach reduces event queuing at the incoming event queue, even with a large number of event streams, high arrival rates, and several complex queries. Consequently, the average latency experienced by incoming events is also reduced.
item: Conference-Full-text
Adopting design thinking practices to satisfy customer expectations in agile practices: a case from Sri Lankan software development industry
(IEEE, 2018-05) Prasad, WMDR; Perera, GIUS; Padmini, KVJ; Bandara, HMND; Chathuranga, D
While the application of agile principles leads to better project success, some projects still fail due to insufficient understanding of client’s exact requirements. Agile teams have recently started adopting Design Thinking (DT) practices to better understand what is in customers’ mind. We explore suitable DT practices to satisfy customer expectations in agile teams using inductive reasoning. We first formulated a conceptual framework based on a literature review. We then conducted a set of interviews with fifteen domain experts from ten IT service organizations. Interview findings were then analyzed using the Straussian grounded theory. Customer journey, story mapping, prototypes, POC, and customer profiling were determined to be the most suitable methods to identify the needs of customers. Moreover, practicing human-centered approach through workshops, discussions, team communication, and end-user interaction through UAT were also identified to be effective. We further classified the best practices into five categories as customer’s real need identification, transforming customer’s real needs into pilot solutions, visualizing the pilot solution for customer feedback, idea generation for the pilot solution, and brainstorming. Based on these findings, we also derived a framework to achieve customer satisfaction through the adoption of DT in agile-base projects.
item: Conference-Full-text
Analysis and derivation of optimum operating conditions of lapple cyclone separator by using cfd
(IEEE, 2016-04) De Silva, MSM; Narayana, M; Jayasekara, AGBP; Bandara, HMND; Amarasinghe, YWR
Cyclones are one of the most extensively used gas cleaning equipment in the industry. Current empirical model based cyclone designs and performance prediction have many limitations due to complex nature of the gas-solid flow field. Computational Fluid Dynamic (CFD) simulation could be useful to predict cyclone performance as an alternative approach. This paper represents a CFD simulation of a Lapple cyclone separator using OpenFOAM software. The flow field of cyclone was obtained by using Reynolds averaged Navier-Stockes equations combine with k-ε closure model. Flow field pressure and velocity distribution were obtained from the simulation and they were compared with the literature to evaluate the model validity. Multiphase Particle in Cell (MPPIC) method was used for the particle modeling, in which particle interactions with other particles were represented by models. Tangential gas velocity profile, pressure drop and particulate collection efficiency of cyclone obtained from the model were comparable to experimental results in the literature. Optimum values for inlet gas-solid velocity and particulate loading rate for the Lapple cyclone were obtained by this analysis. Pressure drop variation with gas-solid inlet velocity which has been obtained by this analysis could be useful to minimize the energy requirement while maintaining the required collection efficiency.
item: Thesis-Full-text
An Analysis of data-driven decision-making capabilities of managers in banks
(2018) Marikar, MS; Bandara, HMND
The vast volume of data generated by modern organizations could be used to gain a competitive advantage through the application of data analytics techniques. As such, many organizations are adopting data analytics and business intelligence tools with the aim of obtaining information more easily, gaining important insights, forecasting future events, and getting timely and reliable information to aid them in their decision making. While these tools are becoming mature, affordable, and easier to use, it is also important to understand whether the contemporary managers in these organizations are ready for Data-Driven Decision Making (DDDM). Therefore, it is imperative to understand to what extent the Decision Makers (DMs) are utilizing these data and tools, whether they can interpret the various forms of outputs from these tools, and gauge their ability to apply those insights to gain a competitive advantage. This study aims to answer these questions through a qualitative survey and a detailed analysis of several cases where such data analytics tools were used. This research uses Straussian’s grounded theory as the tool to analyze and build the theory for this investigation. The analysis focused on commercial banks in Sri Lanka and interviewed DMs at branch and regional levels, and the CTO, CIO, and Head of IT of six banks. It was identified that in many occasions, the DMs’ intuition overrules the DDDM due to uncertainty, lack of trust, knowledge, and the unwillingness towards risk-taking. It was also found that while experienced DMs prefer intuition-based decision-making, novice DMs are more adept at DDDM. Moreover, it was identified that quality of visualizations and presentations had a significant impact on the use of intuition by overruling DDDM. Subsequently, a set of recommendations are provided on the adoption of BI tools and on overcoming the struggles faced while performing DDDM.
item: Conference-Full-text
Ananya - a named-entity-recognition (ner) system for sinhala language
(IEEE, 2016-04) Manamini, SAPM; Ahamed, AF; Rajapakshe, RAEC; Reemal, GHA; Jayasena, S; Dias, GV; Ranathunga, S; Jayasekara, AGBP; Bandara, HMND; Amarasinghe, YWR
Named-Entity-Recognition (NER) is one of the major tasks under Natural Language Processing, which is widely used in the fields of Computer Science and Computational Linguistics. However, the amount of prior research done on NER for Sinhala is very minimal. In this paper, we present data-driven techniques to detect Named Entities in Sinhala text, with the use of Conditional Random Fields (CRF) and Maximum Entropy (ME) statistical modeling methods. Results obtained from experiments indicate that CRF, which provided the highest accuracy for the same task for other languages outperforms ME in Sinhala NER as well. Furthermore, we identify different linguistic features such as orthographic word level and contextual information that are effective with both CRF and ME Algorithms.
item: Conference-Full-text
Application of canonical correlation analysis to study the influence of mathematics on engineering programs: a case study
(IEEE, 2016-04) Nanayakkara, KADSA; Peiris, TSG; Jayasekara, AGBP; Bandara, HMND; Amarasinghe, YWR
Mathematical knowledge is essential to improve the analytical thinking of engineering undergraduates. Exploring more information from existing academic data is an essential aspect of the educational research. The objective of this study is to explore the impact of mathematics performance on different engineering programs. The study was conducted with 626 engineering students from seven different disciplines at the Faculty of Engineering, University of Moratuwa, Sri Lanka. Canonical Correlation Analysis (CCA) was employed to investigate the relationship between mathematics courses and other engineering courses with respect to their disciplines. Results of CCA revealed that the mathematics performance in both semester 1 and 2 influences significantly on the students’ academic performance in Level 2 of the seven engineering disciplines considered. Wilk’s lambda test statistic confirmed that only the first canonical variate pair is significant for all disciplines. The squared canonical correlations of first canonical variate pair indicated that the amount of variance between the mathematics performance and academic performance in Level 2 explained varied among seven disciplines from 42% to 68%. The impact is higher from mathematics in semester 2 than that from semester 1 in all disciplines except for Material Science and Engineering discipline. The explainable variability of student academic performance in Level 2 by the canonical variate of mathematics is varied from 27% to 50% among seven disciplines. Based on preliminary analysis, it can be concluded that the performance in mathematics in Level 1 could indicate the trend towards the student academic performance in all engineering programs.
item: Conference-Full-text
Applying agile practices to avoid chaos in user acceptance testing: a case study
(IEEE, 2016-04) Padmini, KVJ; Perera, I; Bandara, HMND; Jayasekara, AGBP; Bandara, HMND; Amarasinghe, YWR
Agile practices have gained increasing popularity in Information Technology (IT), Education, Marketing, and Advertising industry, as it brings quality products into the market faster. Scrum, Lean Development, and Extreme Programming are the most commonly considered processes under the Agile umbrella. Scrum or scrum variants form a high performance, collaborative team to handle projects that are more complex. We examine the applicability of the scrum framework to a large-scale revenue management system for User Acceptance Testing (UAT). Industry believes integration and acceptance testing is not easy to perform within the scrum framework. Nevertheless, very little is explored about the acceptance testing in Agile practices. We fill this gap by empirically evaluating UAT of a complex, large-scale system (in a public sector organization) to showcase the applicability of scrum framework. While the initial UAT team consisted of 100 domain experts, no process was defined for the UAT. This made it easier to streamline the UAT into the scrum framework. Once the scrum framework was introduced significant improvements in the UAT team was experienced with improved morale, productivity, efficiency, and time to market while having a smooth flow.
item: Conference-Full-text
An automated decision-making framework for precipitation-related workflows
(Faculty of Information Technology, University of Moratuwa., 2020-12) Adikari, AMH; Bandara, HMND; Herath, S; Chitraranjan, C; Karunananda, AS; Talagala, PD
Due to weather’s chaotic nature, static workflow managers are ineffective in integrating multiple Numerical Weather Models (NWMs) with cascading relationships. Unexpected events like flash floods and breakdown in canal water control systems or reservoirs make decision-making in workflow management further complicated. To enable dynamic decision-making, we need to update part or entire workflow, terminate unfitting NWM executions, and trigger parallel NWM workflows based on recent results from NWMs and observed conditions. Most of the existing weather-related decision support systems cannot trigger or create workflows dynamically. They are also designed for specific geography or functionality, making it challenging to customize for regions with different weather patterns. In this paper, we present an automated decision-making framework for precipitation-related workflows. The proposed framework can manage complex weather-related workflows dynamically in response to varying weather conditions, automatically control and monitor those workflows, and update workflow paths in response to unexpected weather events. Using significant flood-related datasets from the Colombo catchment area, we demonstrate that the proposed framework can achieve 100% accuracy in dynamic workflow generation and path updates compared to manual workflow controlling. Also, we demonstrate that unexpected event identification and pumping station controlling workflow triggers could be improved with advance rule sets.
item: Conference-Full-text
An automatic classifier for exam questions with wordnet and cosine similarity
(IEEE, 2016-04) Jayakodi, K; Bandara, M; Meedeniya, D; Jayasekara, AGBP; Bandara, HMND; Amarasinghe, YWR
The learning objectives, learning activities and assessment are very much interrelated. Assessment helps to evaluate students learning achievement. Poorly designed assessments usually fail to examine the achievement of intended learning outcome of a course. There are different taxonomies that have been developed to identify the level of the assessment being practiced such as Bloom’s and SOLO. In this research we have studied the use of WordNet with Cosine similarity algorithm for classifying a given exam question according to Bloom’s taxonomy learning levels. WordNet similarity algorithm depends on the extracted verbs from exam question. Cosine similarity algorithm was based on identification of question patterns of exam question. It consists of tag pattern generation module, grammar generation module, parser generation and cosine similarity checking module. This algorithm was helpful to classify the exam question where verbs were not present in exam questions. Exam questions taken from courses at the Department of Computing and Information Systems at Wayamba University were used as a basis for a performance comparison, with the autonomous system providing classifications that were consistent with those provided by domain experts on approximately 71% of occasions.
item: Conference-Full-text
Biodegradation of natural rubber latex by a novel bacterial species isolated from soil
(IEEE, 2016-05) Hapuarachchi, SNS; Kariyapper, SR; Gunawardana, MBDMD; Egodage, S; Ariyadasa, TU; Jayasekara, AGBP; Bandara, HMND; Amarasinghe, YWR
A natural rubber degrading bacteria Paenibacillus lautus was isolated from soil samples of a rubber plantation in Sri Lanka. The strain was able to decompose natural rubber latex by adhesively growing on its surface using NR latex as the sole carbon source. The staining test performed using Schiff's reagent confirmed the degradation of NR latex. The Fourier Transform Infrared Spectroscopy further verified the result by showing the reduction of C=C double bonds and the presence of carboxylic acids and ketones in the polymer chain. The surface erosion images of the latex overlay surfaces obtained from scanning electron microscopy also validated the degradation process.
item: Conference-Full-text
Biomimetic flexible robot arm design and kinematic analysis of a novel flexible robot arm
(2016-04) Deashapriya, KP; Sampath, PAG; Wijekoon, WMSB; Jayaweera, ND; Kulasekera, AL; Jayasekara, AGBP; Bandara, HMND; Amarasinghe, YWR
Conventional robot manipulators have singularities in their workspaces and constrained spatial movements. Flexible and soft robots provide a unique solution to overcome this limitation. Flexible robot arms have biologically inspired characteristics as flexible limbs and redundant degrees of freedom. From these special characteristics, flexible manipulators are able to develop abilities such as bend, stretch and adjusting stiffness to traverse a complex maze. Many researchers are working to improve capabilities of flexible arms by improving the number of degrees of freedoms and their methodologies. The proposed flexible robot arm is composed of multiple sections and each section contains three similar segments and a base segment. These segments act as the backbone of the basic structure and each section can be controlled by changing the length of three control wires. These control wires pass through each segment and are held in place by springs. This design provides each segment with 2 DOF. The proposed system single section can be bent 90o with respective to its centre axis. Kinematics of the flexible robot is derived with respect to the base segment.
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
Capacitance and tan δ measuring equipment for high voltage insulation modelling and simulation modelling and simulation
(IEEE, 2016-05) Gamage, CM; Nupehewa, JM; Kodikara, KKCS; Chathuranga, SAD; Samarasinghe, R; Lucas, JR; Jayasekara, AGBP; Bandara, HMND; Amarasinghe, YWR
Capacitance and tan δ measurements are usually carried out to check the healthiness of an insulation. Measuring equipment based on different methodologies to test insulation in cables, transformer bushings etc. are available. This paper presents the development of such a measuring equipment for a high voltage (HV) laboratory of a University. The design is divided into three parts as filter unit, test unit, and the measuring unit. These units are separately modeled and simulated using software (MATLAB and PSpice). Filter unit and the test unit are combined to analyze the results through simulation. Simulation results are used to improve the design.
item: Conference-Full-text
Categorizing food names in restaurant reviews
(2016-04) Prakhash, S; Nazick, A; Panchendrarajan, R; Brunthavan, M; Ranathunga, S; Pemasiri, A; Jayasekara, AGBP; Bandara, HMND; Amarasinghe, YWR
There are many aspects such as food, service, and ambience that a customer would look for, when deciding on a restaurant to dine in. Among these aspects, the type of food it sells and the food quality are the most important. Therefore, when automatically rating restaurants based on customer reviews, the food aspect plays a major role. There exists some research on rating individual food items in a restaurant. However, a potential customer requires not the ranking of an individual food item, but the ranking of a particular food category in general. In order to do that, a categorization of food names is required. This paper presents two techniques for food name categorization using document similarity measurements.
item: Conference-Full-text
Challenges faced by agile testers: a case study
(IEEE, 2018-05) Padmini, KVJ; Kankanamge, PS; Bandara, HMND; Perera, GIUS; Chathuranga, D
In the agile framework developers and testers are part of a hyper-productive, self-organizing team. Testing scope changes when user stories are added, updated, or deleted. Moreover, test cases need to be re-written or update when user stories change or removed from the sprint, which wastes time and makes agile testers frustrated. Furthermore, the mini-waterfall model adopted within a sprint could develop unwanted stress in agile testers. Despite these challenges little seem to be understood about the challenges faced by agile testers. We fill this gap by closely studying the challenges faced by agile testers in a multinational IT services organization. We first set up a forum for agile testers to discuss their challenges, malpractices, and best practices. We then conducted an online survey based on the findings from the forum and literature review. Through this, we identified 15 challenges and best practices to overcome those 15 challenges. We further conducted a set of interviews with the subject matter expertise to identify a suitable set of solutions such as conducting retrospective in a fun and engaging way, managing story lifecycle using collaborative tools, setting up ground rules for geographically distributed teams, and introducing innovative sprints.
item: Conference-Full-text
Cheap food or friendly staff? weighting hierarchical aspects in the restaurant domain
(IEEE, 2016-05) Panchendrarajan, R; Murugaiah, B; Prakhash, S; Ahamed, MNN; Ranathunga, S; Pemasiri, A; Jayasekara, AGBP; Bandara, HMND; Amarasinghe, YWR
In aspect-level opinion mining, each aspect is assigned a rating based on customer reviews. More often than not, these aspects exhibit a hierarchical relationship, and the restaurant domain is no difference. With the existence of such hierarchical relationships, rating of an aspect is based on the composite score of its sub-elements. However, the influence of these sub-aspects on the score of a parent aspect is not uniform, since some sub-aspects are perceived more important than others. Therefore, when calculating the composite score for an aspect, influence of each sub-aspect should be weighted according to its perceived importance. Identifying weights for different aspects is addressed as the problem of multi-attribute weighting. However the existing approaches do not utilize the relationships between aspects to find weights. This paper presents an approach to find weights for aspects that exhibit hierarchical relationships in restaurant domain using an improved version of the Analytic Hierarchy Process (AHP), one of the Multi Attribute Decision Making Techniques (MADTs). Different aspects of the restaurant domain are modeled as a hierarchy and weights for aspects are calculated using AHP. Occurrence counts of aspects in restaurant reviews are used to obtain the relative importance of aspects. This approach provides acceptable consistency ratios for the pairwise comparison matrices obtained for each level in the hierarchy of aspects.
item: Conference-Abstract
Cloud-based driver monitoring and vehicle diagnostic with OBD2 telematics
Amarasinghe, M; Kottegoda, S; Liyana Arachchi, A; Muramudalige, S; Bandara, HMND; Azeez, A
We present a cloud-based vehicular data acquisition and analytics system for real-time driver behavior monitoring, trip analysis, and vehicle diagnostics. Our system consists of an On Board Diagnostics (OBD) port to Bluetooth dongle, a mobile app running on a smart phone, and a cloud-based backend. We use a Complex Event Processor (CEP) at both the smart phone and the backend to detect and notify unsafe and anomalous events in real time. For example, CEP engine at the smart phone can alert the driver about rising coolant temperature and rapid fuel drops. It also provides a trip log and filter out what messages to be send to the backend, saving both the bandwidth and power. CEP on the cloud detects reckless driving in real time based on the sensor data provided through the OBD port. Historical data is also used by the backend CEP engine to detect driving anomalies and to predict impeding sensor failures. The mobile app visualizes both real-time data from sensors and alerts. A web-based interface is provided to access the backend information. We tested the system on actual vehicles and demonstrated that the computing, bandwidth, and power consumption of the smart phone is reasonable. App is currently available in Google Play.
item: Conference-Full-text
Command governor adaptive control for unmanned underwater vehicles with measurement noise and actuator dead-zone
(IEEE, 2016-04) Makavita, CD; Nguyen, HD; Jayasinghe, SG; Ranmuthugala, D; Jayasekara, AGBP; Bandara, HMND; Amarasinghe, YWR
Unmanned Underwater Vehicles (UUVs) are being deployed in advanced applications that require precise manoeuvring close to complex underwater structures such as oilrigs and subsea installations or moving objects such as submarines. The effect of vehicle hydrodynamic parameter variations is significant in such scenarios and in extreme conditions the UUV may experience loss of control. In addition, external disturbances present in these environments degrade the controllability of the UUV. Adaptive control has been identified as a promising solution that can improve the controllability in such situations. Nevertheless, adaptive control is not widely used within the industry mainly due to the trade-off between fast learning and smooth control signals. The Command Governor Adaptive Control (CGAC) has recently been proposed as a better compromise between the two extremes. In this paper, the performance of CGAC is investigated in the presence of measurement noise and actuator dead-zone. Simulation results show that that the CGAC is highly effective in retaining good tracking performance even in the presence of significant noise within the feedback signals and an unknown dead-zone in the actuator.