Browsing by Author "Kodagoda, N"

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Analysis and enhancements of a cognitive based complexity measure
(IEEE, 2017-06-25) De Silva, D. I; Kodagoda, N; Kodituwakku, S. R; Pinidiyaarachchi, A. J
As stated by Tom DeMacro, something that cannot be measured is uncontrollable. Thus, a number of metrics have been developed to measure the complexity associated with software by considering various aspects such as size, control flow and data flow between modules, cognitive informatics etc. Amongst these aspects, cognitive informatics is recognized as a promising aspect in measuring software complexity. Thus, majority of the complexity metrics that were proposed after the introduction of cognitive informatics have been proposed mainly based on the cognitive aspect. Amongst them, Chhillar and Bhasins' weighted composite complexity measure is one of the few metrics that had attempted to measure the complexity of a program by considering more than three or more complexity factors. After a thorough analysis, in a previous study, the authors identified that the weighted composite complexity measure could be further improved by considering more complexity factors. This paper extends the previous study to identify the most appropriate factors that could be considered by the weighted composite complexity measure. Using the opinions of the industry experts, the authors were able to discover that compound conditional statements, threads and recursion could also be considered by the weighted composite complexity measure. Accordingly, the weighted composite complexity measure was enhanced to capture the complexities that arise due to those factors. The paper also includes a demonstration of the complexity calculation method of the improved weighted composite complexity measure with the use of three sample java programs, which were written by incorporating the above mentioned factors. In addition, an application of the weighted composite complexity measure to the same programs are also given in the paper, to illustrate the changes in complexity values of the two measures.
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Applicability of three complexity metrics
(IEEE, 2012-12-12) De Silva, D. I; Kodagoda, N; Perera, H
Over the years a number of complexity metrics have been proposed. However, there have been only a few studies conducted to compare those proposed metrics in terms of their practical applicability. The few researches that have been conducted to assess the applicability of a complexity metric have also used the five properties proposed by Briand et al. However determining whether a complexity measure satisfies some theoretical complexity properties is not a reliable method of determining the practical applicability of it. Thus, the main intent of this study was to compare three proposed code complexity metrics: McCabe's cyclomatic complexity, Halstead's software science and Shao and Wangs' cognitive functional size and identify which metric is the most suitable metric that can be used in the current state of the art with the help of thirty programmers. To conduct this empirical study ten freely available java programs were used as the base. From this study it was identified that Shao and Wangs' cognitive functional size is the best complexity metric that can be used in the real world.
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Applicability of Weyuker's properties using three complexity metrics
(IEEE, 2013-04-26) De Silva, D. I; Kodagoda, N
Although a number of complexity metrics have been proposed, only a few studies have been conducted to compare those proposed metrics to find the most effective and comprehensive metric. In general, to find the effectiveness and the comprehensiveness of a metric Weyuker's nine properties are used. However determining whether a complexity metric satisfies some theoretical framework is not enough to determine the effectiveness and comprehensiveness of that particular metric. Thus, this empirical study was conducted to find the effectiveness and comprehensiveness of three complexity metrics - McCabe's cyclomatic complexity, Halstead's software science and Shao and Wangs' cognitive functional size using the help of thirty software programmers with five or more years of working experience and thereby demonstrate the applicability of Weyuker's properties.
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Automatic Question Extractor and Answer Detector in a Recorded Webinar
(IEEE, 2022-08-18) Dissanayake, C; Kodagoda, N; Suriyawansa, K
Online learning becomes the primary method of education due to the novel coronavirus (COVID 19). This research paper describes the automatic extraction of domain-related questions in a lecture video, identifies the answers given by the lecturer for both voice-based questions and chat questions. The paper also presents a method to identify whether a lecturer gave a valid answer for the chat-based questions in the later section of the video. Additionally, this paper describes the approach to identify the most accurate solutions from the custom search engine-based responses.
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A Bilingual Audio Based Online Shopping Mobile Application for Visually Impaired and the Elderly People
(IEEE, 2021-12-07) Kangeswaran, V; Vasandarai, D; Eliyas, C; Munsil, M. M. M; Kodagoda, N; Suriyawansa, K
Despite the widespread success of online shopping, it is not available to all consumer types. In this sense, visually impaired and elderly users, in particular, frequently face daunting barriers. Due to the inaccessibility and difficulty of current online shopping mobile applications, millions of visually impaired and elderly people are unable to benefit from the convenience provided by online shopping. Developing ideas that inspire people is really essential for visually impaired and elderly people to engage in social life. Generic product explanations, unhelpful images, and visually appealing user experiences are provided to average eyes in online shopping, and they are incompatible with visually impaired people, even with visually impaired assistive devices. Due to visual barriers and inaccessible user experiences, the visually impaired are struggling to do online shopping independently. During this COVID-19 pandemic situation, online shopping is one of the better ways to meet everyone's needs and wants. Ordinary individuals can meet their needs and desires, but the visually impaired and elderly people who live alone find it difficult to manage their daily life. Therefore, we have come up with a solution for this by having an online shopping mobile application. Our objective with this application is to assist visually impaired and elderly individuals in meeting their underlying needs and to help them in this pandemic situation. This paper presents an online shopping mobile application for visually impaired and elderly people that allows them to shop online in a variety of convenient ways.
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The Blue Zone-Mobile Bluetooth Network Expansion
(IEEE, 2018-12-12) Shafie, A. F. R; Ikram, M. M. M; Liyanage, C. S; Alahakoon, A. E; Liyanage, N. M; Kodagoda, N
Bluetooth is a widely available technology in today's mobile phones. It enables devices to communicate wirelessly without being in the line of site of other devices. Regrettably, similar to the majority of the technologies that exists today, Bluetooth has its own shortcoming, it is that it's limited by range and applicable only between two Bluetooth enabled mobile phones at a time. Based on the current Ad-hoc On-demand Distance Vector routing (AODV) protocol used to create ad-hoc networks, and providing some enhancements to it, the Blue Zone application proposes an ad-hoc network solution to overcome the limitations of the mobile Bluetooth technology.
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Centralized Road Infrastructure Information Collection and Processing System for Sri Lanka
(IEEE, 2018-12-21) Musthafa, M; Magenthirarajah, S; Rauf, A. A; Balendran, K; Kodagoda, N; Sriyaratna, D
The following topics are dealt with: learning (artificial intelligence); mobile computing; feature extraction; support vector machines; natural language processing; image classification; Internet; security of data; power engineering computing; decision trees.
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Comparative Study of Parameter Selection for Enhanced Edge Inference for a Multi-Output Regression model for Head Pose Estimation
(Institute of Electrical and Electronics Engineers Inc., 2022-11-04) Lindamulage, A; Kodagoda, N; Reyal, S; Samarasinghe, P; Yogarajah, P
Magnitude-based pruning is a technique used to optimise deep learning models for edge inference. We have achieved over 75% model size reduction with a higher accuracy than the original multi-output regression model for head-pose estimation
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Comparision Between Features of CbO based Algorithms for Generating Formal Concepts
(IGI Global, 2016-01-01) Kodagoda, N; Pulasinghe, K
Formal Concept Analysis provides the mathematical notations for representing concepts and concept hierarchies making use of order and lattice theory. This has now been used in numerous applications which include software engineering, linguistics, sociology, information sciences, information technology, genetics, biology and in engineering. The algorithms derived from Kustenskov's CbO were found to provide the most efficient means of computing formal concepts in several research papers. In this paper key enhancements to the original CbO algorithms are discussed in detail. The effects of these key features are presented in both isolation and combination. Eight different variations of the CbO algorithms highlighting the key features were compared in a level playing field by presenting them using the same notation and implementing them from the notation in the same way. The three main enhancements considered are the partial closure with incremental closure of intents, inherited canonicity test failures and using a combined depth first and breadth first search. The algorithms were implemented in an un-optimized way to focus on the comparison on the algorithms themselves and not on any efficiencies provided by optimizing code. The main contribution of this paper is the complete comparison of the three main enhancements used in recent variations of the CbO based algorithms. The main findings were that there is a significant performance improvement partial closure with incremental closure of intents is used in isolation. However, there is no significant performance improvement when the depth and breadth first search or the inherited canonicity test failure feature is used in isolation. The inherited canonicity test failure needs to be combined with the combined depth and breadth first feature to obtain a performance increase. Combining all the three enhancements brought the best performance.
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Comparision Between Features of CbO based Algorithms for Generating Formal Concepts
(IGI Global, 2016-01-01) Kodagoda, N; Pulasinghe, K
Formal Concept Analysis provides the mathematical notations for representing concepts and concept hierarchies making use of order and lattice theory. This has now been used in numerous applications which include software engineering, linguistics, sociology, information sciences, information technology, genetics, biology and in engineering. The algorithms derived from Kustenskov's CbO were found to provide the most efficient means of computing formal concepts in several research papers. In this paper key enhancements to the original CbO algorithms are discussed in detail. The effects of these key features are presented in both isolation and combination. Eight different variations of the CbO algorithms highlighting the key features were compared in a level playing field by presenting them using the same notation and implementing them from the notation in the same way. The three main enhancements considered are the partial closure with incremental closure of intents, inherited canonicity test failures and using a combined depth first and breadth first search. The algorithms were implemented in an un-optimized way to focus on the comparison on the algorithms themselves and not on any efficiencies provided by optimizing code. The main contribution of this paper is the complete comparison of the three main enhancements used in recent variations of the CbO based algorithms. The main findings were that there is a significant performance improvement partial closure with incremental closure of intents is used in isolation. However, there is no significant performance improvement when the depth and breadth first search or the inherited canonicity test failure feature is used in isolation. The inherited canonicity test failure needs to be combined with the combined depth and breadth first feature to obtain a performance increase. Combining all the three enhancements brought the best performance.
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Consumer and Farmer Centric Subscription Based Organic Vegetable/Fruit Delivery System
(IEEE, 2021-12-09) Karunarathna, T. M. N. P; Kumari, M. M. A; Kulasinghe, W. D. K. A; Liyanage, T. L. P; Kodagoda, N; Suriyanwsa, K; Kumari, D
For centuries, the economy of Sri Lanka has been backed by the agricultural sector. Even though it has contributed to the development of the nation on a large scale, the economies and living standards of the farmers have not been improved much. Most of the farmers remain poor mainly due to not knowing the market demand and the low buying prices of the middleman. Meanwhile, the consumers in Sri Lanka are buying non-organic vegetables and fruits which are highly contaminated with dangerous chemicals which in turn has contributed to the rapidly increasing non-communicable disease rates in both consumers and farmers. The proposed system is an attempt to solve these problems faced by both farmers and consumers by reducing the farmers-consumer knowledge gap and providing consumers a trustworthy and personalized subscription for organic vegetables/fruits with a donation platform.
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Database Scaling on Kubernetes
(IEEE, 2021-12-09) Perera, H. C.S; De Silva, T. S. D; Wasala, W. M. D. C; Rajapakshe, R. M. P. R. L; Kodagoda, N; Samaratunge, U. S. S; Jayanandana, H. H. N. C
Kubernetes is a hot topic in the field of Software Engineering and Distributed Computing. When compared to previous methods, the principle underlying Kubernetes, which is containerization, has altered how applications are created and delivered. However, when considering the state, particularly the databases, with Kubernetes, there is a scalability and data synchronization barrier. The most frequently used approach is to host the database outside of Kubernetes and maintain connectivity with the cluster. Kubernetes inherent capabilities are sufficient for hosting databases. But that requires high domain knowledge to do the configurations and maintain the databases on Kubernetes. The purpose of this research is to fulfil that gap by introducing a solution for managing highly available databases on Kubernetes. The solution is limited to managing PostgreSQL databases on Kubernetes using auto-scaling. A novel algorithm is proposed for auto-scaling, as previous algorithms do not take database requests into account when determining the scaling need. The drawbacks of data synchronization and auto-scaling will be solved in this research, and the end user will be able to access the service without interruption for the majority of the time, as the final solution makes the database cluster highly available for the service layer.
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Deep Vision-Data Mining To Find Insights and Visualization in Code Repositories
(Institute of Electrical and Electronics Engineers, 2022-09-16) Ariyarathne, I.G.P.S; Wimalasuriya, M.K; Abesinghe, N.D.N.S; Edirisinghe, E.A.S.H.; Kodagoda, N; Kasthurirathna, D
Deep Vision is a code mining system for analyzing and visualizing a repository's codebase so that its users may obtain a sense of the repository's insights. This system will examine codebases and support as many languages as feasible. This system visualizes the file structure, vocabulary and length change rates, comprehensibility and defect rates, etc. It is vital to have a comprehensive grasp of the codebase to manage the program's complexity by calculating multiple factors and presenting them in a descriptive and engaging dashboard to enhance the quality of the software process and the project's controllability. Improved code visualization may help improve code understandability while lowering development costs. In addition, our visualization regions and methodologies are one-of-a-kinds. To get rapid and reliable results, we will create new machine learning models and algorithms for analysis and new categories of a code repository. Our dataset for this research will be GitHub open-source code repositories
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Digital Platform to Empower the Self-Employment in Sri Lanka
(IEEE, 2021-12-01) Wickramasinghe, H. C. P; Thebuwana, T. D; Wijesinghe, G. K. H. S; Dissanayake, U. N; Kodagoda, N; Suriyawansa, K
Unemployment is a huge problem around the world because a lack of job opportunities. People are unable to find the job opportunities according to their preferences and qualifications. As a solution for this, many countries are attempting to empower self-employment. Most of current world problems have been solved using modern technologies. Therefore, the development of self-employment also can be achieved through modern technology. The objective of our proposed platform, HIRELANCER, is empowering self-employment using modern technologies. HIRELANCER is bringing the consumers, service providers, and suppliers into the same platform. HIRELANCER will consist of innovative features that go beyond comparatively to other platforms such as an advanced mechanism to find best suitable service providers/suppliers for the service, handling the virtual front-desk, cost estimation for the services prior to contacting a service provider, and advanced facility to find a suitable career path for the people who are seeking career guidance. This research paper discusses how the innovative features of HIRELANCER will be beneficial for consumers, service providers, and suppliers and ultimately achieve our main objective, which is empowering self-employment in Sri Lanka.
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EDUZONE – A Educational Video Summarizer and Digital Human Assistant for Effective Learning
(IEEE, 2022-12-26) Wangchen, T; Tharindi, P.N; De Silva, K. C. C. C; Sandeepa, W. D. T; Kodagoda, N; Suriyawansa, K
The availability of technology and the expansive nature of the internet have created a surge in the demand for online learning. Despite so many advantages, there are some existing drawbacks related to online learning. The lengthy recorded video lectures of different subjects and modules in a static manner, are extremely tedious for the learner to understand the contents available. And lack of assistance for academic-related problems of students is also stated as a major issue that comes with online education. EDUZONE provides a reliable solution to mitigate and overcome these challenges. This tool is educational assistance that generates a summarized version of the video lectures which depicts the overall idea of the whole video with the capability of a lecture notes generator along with a digital human which helps to clarify students’ problems and build an efficient conversational flow. The summarized video content can be used by the learners for revisions and as a quick reference before any examinations. In addition to generating short and precise content, EDUZONE also indexes any specific topics to make it easier to find content and generate class notes, highlighting all the important content. Overall EDUZONE can be considered a time-efficient educational assistant which helps students with their studies.
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Eigenface based automatic facial feature tagging
(IEEE, 2008-12-12) Wijeratne, S; Jayawardena, S; Jayasooriya, S; Lokupathirage, D; Patternot, M; Kodagoda, N
There are several approaches to search databases of faces. However such methods still require a significant use of humans to interpret an eyewitness account and so forth. In many cases these searches are done using visual building tools as creating a graphical face model. A system that can easily interface with general users should directly search a person by description given verbally or textually. This would reduce costs in the search process. Facial feature characteristics identification would act as a stepping stone in cataloguing large face databases automatically thus providing the possibility of a description based face search by text. This paper presents the possibility of utilizing eigenface approach to recognize different characteristics of a facial feature and assigning descriptive words such as "Large", "Small" to each feature. After training the system, it would automatically attempt to match a pattern in the training set that best describes the input image and output a tag associated with it. This effectively allows an image of a person's face to be tagged by his or her feature characteristics. While utilizing the standard set steps as defined in the eigenface algorithm, slight modifications are done in the algorithm that matches input images with ones in the training set. The training set defined has a very huge impact for the final outcome, and due to the subjective nature of the training, future research would be done on this regard. The investigation showed that the method works fine with well defined features such as eyes but fails for features such as foreheads due to the lack of significant differences or characteristics between such features. Hence it is seen that while eigenface can be used for the categorization of well defined features, it is unable by itself to create a system that can cover all features of a face.
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Enhancements to an OO Metric: CB Measure.
(Journal of Software, 2018-01-01) De Silva, D. I; Kodituwakku, S. R; Pinidiyaarachchi, A. J; Kodagoda, N
Due to the wide usage of the object-oriented paradigm as a development paradigm many researches have proposed metrics to measure the complexity of object-oriented programs. The proposed object-oriented metrics can be divided into two categories based on the main aspect they have considered: metrics based on object-oriented aspects and metrics based on the cognitive aspects. Majority of the metrics which belong to the latter category have relied on a maximum of three complexity factors to derive the complexity of a program. CB measure is one of the few metrics that has considered four or more complexity factors to measure the complexity associated with a software program. However, there exists some other factors that could be considered by the CB measure to make it a more practically applicable measure. Such factors were proposed by the authors in a previous study. This paper demonstrates how those factors can be incorporated to the CB measure. In addition, it validates the practical applicability of the modified CB measure.
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Exploiting Multivariate LSTM Models with Multistep Price Forecasting for Agricultural Produce in Sri Lankan Context
(IEEE, 2020-12-10) Navaratnalingam, S; Kodagoda, N; Suriyawansa, K
In Sri Lanka agricultural produces possess a large supply which involves various stakeholders and thus, fluctuation of the agricultural produce prices has a direct impact on the purchasing decisions of the consumer. So, the main purpose of this study is to address the problem faced by the consumer due to poor awareness of price fluctuation which consequently astonish the consumers and hinder them from making better purchasing decisions. The research study is being specially developed in a way to adapt the Sri Lankan agricultural consumer market that is mainly based on Pettah and Dambulla trade centers. As the study we exploited different types of LSTM model with multivariate inputs along with the different combination of multistep models. The result of the study reveals that better performance was obtained for the multivariate CNN LSTM model with encoder decoder multistep model which provided an average RMSE of 19.46 Sri Lankan rupees per kilogram with an average RMSPE of 14.9%. Also, study reveals a correlation between price fluctuation and standard days of the week, where a better prediction was obtained for Monday and Tuesday with an average RMSE of 17.2 and 17.7 Sri Lankan rupees per kilogram respectively with an average RMSPE of 12.2%. Based on the input timestep considered for model, though 14 days and 21 days provided a similar result with minor variation result reveals that 14 days provided a lesser standard deviation of 0.17 than 21 days standard deviation which is 0.98.
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A Fully Functional Shopping Mall Application--SHOPPING EYE
(IEEE, 2014-11-18) Karunarathna, K. M. D. M; Weerasingha, H. M. D. A; Rumy, M. M; Rajapaksha, M. M; De Silva, D. I; Kodagoda, N
In the modern world, shopping has become an essential day to day activity for most of the people. However, their busy life style has lessened the time to do shopping. This has made them to look for quicker and easier ways to do their shopping. Some of the difficulties that people have to go through when they do shopping include having to travel a long distance without knowing the availability of the items, difficulty in finding relevant shops inside a shopping mall, forgetting to buy some items which they intended to buy. In order to overcome the above mentioned problems a fully functional shopping mall application is proposed in this paper. It contains details about all the shops inside a mall, available items, customer wish lists and a map. It consists of a mobile application developed using Android and a Server side module which act as a main database server for connecting with customers and shop owners. Both the modules communicate through web services. In this project wireless communication technique -- Bluetooth is used to identify the vertical and horizontal position of the customer. Augmented reality based technique is used to tag the shops with its promotions, loyalty points etc.
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A Fully Functional Shopping Mall Application--SHOPPING EYE
(IEEE, 2014-11-18) Karunarathna, K. M. D. M; Weerasingha, H. M. D. A; Rumy, M. M; Rajapaksha, M. M; De Silva, D. I; Kodagoda, N
In the modern world, shopping has become an essential day to day activity for most of the people. However, their busy life style has lessened the time to do shopping. This has made them to look for quicker and easier ways to do their shopping. Some of the difficulties that people have to go through when they do shopping include having to travel a long distance without knowing the availability of the items, difficulty in finding relevant shops inside a shopping mall, forgetting to buy some items which they intended to buy. In order to overcome the above mentioned problems a fully functional shopping mall application is proposed in this paper. It contains details about all the shops inside a mall, available items, customer wish lists and a map. It consists of a mobile application developed using Android and a Server side module which act as a main database server for connecting with customers and shop owners. Both the modules communicate through web services. In this project wireless communication technique -- Bluetooth is used to identify the vertical and horizontal position of the customer. Augmented reality based technique is used to tag the shops with its promotions, loyalty points etc.