Research Papers - Dept of Information Technology

Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/593

Browse

Now showing 1 - 20 of 426

Open Access
Abstract concepts: A contemporary requirement for Rich Internet Applications engineering
(2016) Dissanayake, N. R; Dias, G. K. A
Rich Internet Applications are very advanced and complex systems, and for their development there are numerous tools, frameworks, libraries, techniques, and technologies are available. The underplaying concepts of the Rich Internet Applications are still have not been defined well, and the tools, frameworks, or libraries do not improve these underlying concepts; instead they might use their own forms of the concepts. If we can understand the abstract fundamental concepts of Rich Internet Applications, we can gain some advantages like: increased realization, knowledge sharing, and lower learning curves. These aspects have not being much discussed or researched within the domain; therefore, we attempt to pinpoint the importance of having abstract concepts for Rich Internet Applications engineering, as a contemporary requirement. This knowledge will help to look at the researching in Rich Internet Application engineering in a different perspective, and will lead to introduce abstract concepts, for Rich Internet Applications.
Embargo
Adapting MaryTTS for Synthesizing Sinhalese Speech to Communicate with Children
(IEEE, 2021-12-01) Lakmal, M. A. J. A; Methmini, K. A. D. G; Rupasinghe, D. M. H. M; Hettiarachchi, D. I; Piyawardana, V; Senarathna, M; Reyal, S; Pulasinghe, K
The majority of the Sri Lankan population speak Sinhala, which is also the country's mother tongue. Sinhala is a difficult language to learn by children aged between 1–6 years when compared to other languages. Text to speech system is popular among children who have difficulties with reading, especially those who struggle with decoding. By presenting the words auditorily, the child can focus on the meaning of words instead of spending all their brainpower trying to sound out the words. In Sri Lanka, however, computer systems based on the Sinhala language especially for children are extremely rare. In this situation having a Sinhala text-to-speech technology for communicating with children is a helpful option. Intelligibility should be considered deeply in this system because this is specific for children. Recordings of a native Sinhalese speaker were used to synthesize a natural-sounding voice, rather than a robotic voice. This paper proposes an approach of implementing a Sinhalese text-to-speech system for communicating with children using unit selection and HMM -based mechanisms in the MaryTTS framework. Although a work in progress, the intermediate findings have been presented.
Embargo
An add-on module to ECU for extending the functionalities of EFI tune-up process: An electronic device which extends the lifetime of fuel injectors
(Faculty of Graduate Studies and Research, 2017-01-26) Pathirana, S.; Gajanayake, C.; Vithanage, C.W.
The paper presents the ideology, procedures followed in order to implement, and the experimental results of an electronic device developed to extend the functionalities of an Electronic Control Unit (ECU) employed in the automobiles equipped with Electronic Fuel Injection (EFI) technology. The EFI system is empowered with a computing unit, ECU. A key responsibility of a typical ECU is to manipulate the fuel delivery for efficient combustion to optimize the engine's performance while minimizing the fuel wastage and emissions. Further, it is expected to self-adjust to fulfill the above requirements relying on several input sensors including a feed-back sensor. But, due to various reasons the objective is not fully achieved, therefore need to be rectified time to time. The process is called EFI Tune-up. Sensor malfunction and decayed fuel injectors are the major reasons for the incapability of ECU to control the situation. The especially developed add-on module was designed to assist the ECU when it loses its tolerance because of decayed fuel injectors and once the feedback sensor is beyond its range of operation. The strategy followed was to modify the Injector Pulse Width, a Pulse Width Modulated (PWM) control signal generated by the ECU to regulate the fuel release of fuel injectors, based on an analysis done regarding the emissions containing in exhaust gas. The experimentally obtained evaluation records conclude that the involvement of the introduced add-on module could reduce the fuel wastage and release of toxic emissions up to 70%, depending upon the condition of the fuel injector.
Embargo
Adding Commonsense to Robotic Application Using Ontology-Based Model Retraining
(IEEE, 2022-10-04) Pradeepani, M. K. T.; Jayawardena, C.; Rajapaksha, U. U. S.
In terms of the level of technological capability in the world today, the use of automated robotics is common in various fields. There are large projects going on in many industries that collaborate between robots and other robots, as well as humans and robots. In hospital environments, care for people with medical needs and their needs and used to make appropriate suggestions to their problems. Robots can also be found in certain areas that can respond quickly as an emergency rescue agent. Furthermore, robots, which can be seen in the hotel industry as waiters and as farm assistants in agriculture, have a great tendency to be used as multi-tasking agents in many fields. In each of these areas, robots must co-operate with humans. In that situation, the importance of the exchange of mutual knowledge between robots-robots and between humans-robots comes into the picture. What matters here is not only the quantitative vastness of knowledge but also the ability to understand each other in the same medium. Although the common sense that people need in their day-to-day work is completely obvious to humans, the commonsense knowledge domain needs to be implanted in robots. Whatever concept is defined for adding commonsense to robotics, it should be a consistent concept that can be logically constructed so that it can be understood by a machine. As will be discussed later in the paper, different methods have been used in various related works to add a different kind of domain knowledge to robotics. The objective of this paper is to provide an improved retrained model for robotics in order to give them the ability to act more human-like when performing tasks. By using the proposed model robots are able to answer the incomplete command or inquiries related to a given context. One of the objectives of this work is to use the ontology-based, commonsense-support existing knowledge base as a mechanism to retrain and build a new model.
Embargo
Ads-In Site: Location based advertising framework with social network analyzer
(IEEE, 2014-12-10) Perera, A. A. G. A. K; Jayarathne, R. P. E. T; Thilantha, B. Y; Kalupahana, S. I. G; Haddela, P. S; Kirupananda, A; Edirisinghe, E. A. T. D
Social networks contain a vast amount of data that holds very valuable information and is nowadays identified as a very effective source in marketing. The content of social networks can be used to identify the business needs and preferences of people. This research is carried out with the aim of providing suitable advertisements for people based on their preferences by analysing their social network content. Users' demographic details are also considered in providing suitable advertisements of the shops that are most conveniently located for a particular user. The primary goal of this research is to build an advertisement framework that supports targeted advertising by analysing social network content. The information extracted by analysing the content of social networks is used to predict the advertisement categories that interest a particular user. The framework applies location based services to filter advertisements based on the location of the shop.
Open Access
Advance Technology for Kids to Improve Knowledge and Skills using Motion Gesture Recognition – Leap Mania
(SLIIT, 2014-12-16) Nandasiri, K. G. M. P; Nawarathna, N. H. C. E. M; Mohamad, M. M. R; Herath, H. M. C. K; Kasthuriarachchi, K. T. S; Wijendra, D
Leap mania is a gesture controlled e-leaning system which targets the nursery level kids to improve their knowledge and skills in a pleasurable learning environment. Game-based learning is becoming popular in the academic discussion of Learning Technologies. However, even though the educational potential of games has been thoroughly discussed in modern days, teaching to small kids became difficult due to the short attention spans of them. In addition to traditional methods of learning and teaching, such as reading books and newspapers, a huge variety of online educational resources are available to provide an atmosphere of fun and interactive designs to keep children engaged. However, there is no proper e-learning game tools with gesture control mechanism found among the tools and computer based applications for kids. This research focuses on building an enthusiastic and pleasurable learning environment to enhance the knowledge and skills of kids by implementing a game-based learning application using leap motion controller.
Open Access
Agro-Genius: Crop Prediction Using Machine Learning
(https://ijisrt.com/agrogenius-crop-prediction-using-machine-learning, 2019-10) Gamage, M. P. A. W; Kasthurirathna, D; Paresith, M. M; Thayakaran, S; Suganya, S; Puvipavan, P
This paper present a way to aid farmers focusing on profitable vegetable cultivation in Sri Lanka. As agriculture creates an economic future for developing countries, the demand of modern technologies in this sector is higher. Key technologies used for this problem are Deep Learning, Machine Learning and Visualization. As the product, an android mobile application is developed. In this application the users should input their location to start the prediction process. Data preprocessing is started when the location is received to the system. The collected dataset divided into 3 parts. 80 percent for training, 10 percent for testing and 10 percent for validation. After that the model is created using LSTM RNN for vegetable prediction and ARIMA for price prediction. Finally, for given location profitable crop and predicted future price of vegetables are shown in the application. Other than the prediction, optimizing for multiple crop sowing according to the user requirements and visualizing cultivation and production data on map and graphs are also given in the application. This paper elaborates the procedure of model development, model training and model testing.
Embargo
Agro-Mate: A Virtual Assister to Maximize Crop Yield in Agriculture Sector
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Dayalini, S.; Sathana, M.; Navodya, P. R. N.; Weerakkodi, R.W. A. I. M. N.; Jayakody, A.; Gamage, N.
Information Technology plays a vital role in the agriculture industry. The main goal of the project is to develop a mobile application to support farmers to take accurate decisions and help them with activities such as soil quality determination, best crop selection, rice disease prediction, and disaster prediction for the wet zone of Sri Lanka. To achieve the main goal the project has incorporated advanced technologies such as Deep Learning, Image Processing (IP), Internet of Things (IoT), and Machine Learning that can support farmers or investors in a way to maximize yield. ‘Agro-Mate’ application is developed in a way to facilitate the agriculture industry. ‘Agro-Mate’ consists of four components such as soil quality determination and fertilizer recommendation, best crop selection, rice disease prediction and recommendation, and natural disaster prediction and providing the recommendation. Also, the application suggests fertilizer when soil is lacking quality and provides recommendations whenever rice diseases or natural disasters are identified. The usage of android mobile devices in agriculture is one of the key components of the sector's growth, which facilitates the farmer's inaccurate decision-making to gain more quality and quantity of crops. Agro-mate’ is more likely to increase the productivity of crops and indirectly increase the GDP of Sri Lanka.
Embargo
AGventure: Creating a Sustainable Economy by Reducing Food Surpluses and Food Wastages through the Crop Management
(IEEE, 2022-07-18) Hennayaka, H. M.H. H; Dissanayaka, D. M.I. S; Silva, A. M. U; Sakuntha, N. M. K; Dassanayake, D.M.G; Jayasinghe, J. A. D.T. B
Since ancient times, Sri Lanka has always been an agriculturally focused country with agriculture as a top priority. But the economic sustainability of Sri Lanka is deteriorating day by day due to the lack of proper awareness and understanding of crop cultivation among the farmers. Sri Lankan farmers produce more vegetables than they need for home consumption each year, but only a small portion is exported. When an economy has a food surplus, rising costs for certain goods discourage consumers and reduce demand for those goods. As a result, there is a surplus of commodities in the economy and a significant amount of goods are discarded. Food surplus and food wastage are the major problems leading to economic and environmental degradation in Sri Lanka. "AGventure: Creating sustainable economy by reducing food surpluses and food wastage through the crop management." has been proposed as a mobile application-based solution. The primary goal of this research is to better understand the current food surplus and food waste to address the economic and environmental sustainability crisis in Sri Lanka. The proposed mobile application mentioned above will enable farmers to minimize problems arising in all processes from crop forecasting to handing over the products to the consumer for final consumption. The proposed system is mainly based on crop prediction, Price prediction, pest detection, and cloud marketing collaborating with Machine Learning, Deep Learning, and image processing concepts. The main goal of the proposed solution is to control excess and offer a successful solution to the problems that arise in crop cultivation. The research further produced results such as choosing the best crop for the location, predicting future prices, recognizing agricultural diseases throughout the growing season, and stock forecasting through cloud market.
Embargo
AI and Machine Learning Based E - Learning System For Secondary Education
(IEEE, 2022-07-18) Wijayawardena, G. C. S; Subasinghe, S. G. T. S; Bismi, K. H. P; Gamage, A
One of the key functions directly shifted to online platforms under COVID-19 is education. The paper is about an E-learning system for secondary education in Sri Lanka. Learners and teachers can access information, resources, and tools through an E-Learning system, which is a Learning Management System that integrates a number of online activities. The main functions provided through the proposed system are chatbot, final grade prediction and weak area prediction of the students. Chatbots are becoming increasingly popular in a wide range of applications, especially in those that provide intelligence support to the user, according to recent research. So, in order to speed up the aid process, these systems are often integrated with Chatbots, which can quickly and accurately read the user's questions. This paper describes the implementation of a Chatbot prototype in the educational domain: a system for providing support to students. In the beginning, the goal was to design a special architecture and communication model that would help students get the proper answers. The final grade prediction component plays major role in the system. Because when the students are graded by their marks, they can review which areas that they have to improve and work on them. This is helpful for students as well as teachers. Weak area prediction also plays a significant role, because it can help to find out the weak areas of each subject and generate Individual Student Progress Plans to predict the students’ weak subjects and the subject areas of the students. This motivates students to get higher marks easily because this part is mainly focused on weak areas of students and improve those weak areas by providing several learning activities. These are the major parts of this system to have a good E-learning system for both students and Teachers.
Embargo
AI Base E-Learning Solution to Motivate and Assist Primary School Students
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Silva, P.H.D.D.; Sudasinghe, S.A.V.D.; Hansika, P.D.U.; Gamage, M.P.; Gamage, M.P.A.W.
E-learning is a form of providing education by using electronic devices. Lack of proper mechanisms for encouraging and assisting students are key issues faced by many students in an e-learning environment. The ‘Vidu Mithuru’ is a question-based e-learning application which has been developed as a solution to overcome these problems. This mobile application will auto generate and categorize the questions, evaluate the answers and track the performance while providing motivational quotes by detecting the emotions of the student. This mobile application is based on Neural Networks, Natural Language Processing and Machine Learning concepts. In order to developing this application, the information provided by the primary education professionals was used to comply with the standards. The core objective of the proposed solution is to track the performance level and assist the students to improve in their studies while keeping them motivated. The trained Machine Learning models have achieved the accuracy of 75%, 78%, 99% and 86% for question categorization model, speech emotion detection model, facial emotion detection model and model to evaluate answers as respectively. We have received favorable responses as the results after testing the developed ‘Vidu Mithuru’ mobile application
Embargo
An AI based Chatbot to Self-Learn and Self-Assess Performance in Ordinary Level Chemistry
(IEEE, 2020-12-10) Mahroof, A; Gamage, V; Rajendran, K; Rajkumar, S; Rajapaksha, S, K; Wijendra, D
Education is one of the fast-growing fields in the global perspective. Advancement of technology can be used in this sector to provide an effective and a valuable education system. In general, the students are more attracted to displays rather than the textbooks. In Sri Lanka, there is an inadequacy of resources and teachers cannot provide one on one attention to the students. Sri Lanka is not equipped with any platform to self-learn or self-evaluate their performance using an application either. Fortunately, “Edubot” acts as a solution for the stated research gap by providing a self-learning and self-evaluating AI based chatbot platform for Ordinary Level students in Chemistry domain. The self-learning component will provide the students a classroom environment by providing interactive tutorials. Explanatory responses would be given by Edubot by capturing doubts raised by the students and the self-evaluating component will provide an exam-based environment in which the Edubot auto generates the question and answers. The research finding shows that each component has an accuracy of more than 70 percent and helps to achieve the main goal of increasing the resources available to the ordinary level students in the Chemistry domain. This would then lead to an increase in the pass rate of the chemistry subject in the G.C.E Ordinary Level exam.
Embargo
An AI based Chatbot to Self-Learn and Self-Assess Performance in Ordinary Level Chemistry
(2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Mahroof, A.; Gamage, V.; Rajendran, K.; Rajkumar, S.; Rajapaksha, S.; Wijendra, D.
Education is one of the fast-growing fields in the global perspective. Advancement of technology can be used in this sector to provide an effective and a valuable education system. In general, the students are more attracted to displays rather than the textbooks. In Sri Lanka, there is an inadequacy of resources and teachers cannot provide one on one attention to the students. Sri Lanka is not equipped with any platform to self-learn or self-evaluate their performance using an application either. Fortunately, “Edubot” acts as a solution for the stated research gap by providing a self-learning and self-evaluating AI based chatbot platform for Ordinary Level students in Chemistry domain. The self-learning component will provide the students a classroom environment by providing interactive tutorials. Explanatory responses would be given by Edubot by capturing doubts raised by the students and the self-evaluating component will provide an exam-based environment in which the Edubot auto generates the question and answers. The research finding shows that each component has an accuracy of more than 70 percent and helps to achieve the main goal of increasing the resources available to the ordinary level students in the Chemistry domain. This would then lead to an increase in the pass rate of the chemistry subject in the G.C.E Ordinary Level exam.
Embargo
AI-based Behavioural Analyser for Interviews/Viva
(IEEE, 2022-01-03) Dissanayake, D. Y; Amalya, V; Dissanayaka, R; Lakshan, L; Samarasinghe, P; Nadeeshani, M; Samarasinghe, P
Globalization and technology have made virtual interviews to be the choice of recruitment. Even though online interviews/viva have eliminated time, budgetary, and geographical barriers, the lack of comprehension regarding the interviewee’s behavioural aspects is yet to overcome. Therefore, a machine-based approach is proposed in this research for detecting and assessing changes in interviewees’ behaviour and personality traits based on nonverbal cues. Additionally, a group analysis of other applicants, as well as a comparison of the interview environment with the non-interview environment is also being obtained. To achieve this, we focus on the candidate’s emotion, eye movement, smile, and head movements. The system was carried out using deep learning and machine learning models which achieved accuracies over 85% for all smile, eye gaze, emotion, and head pose analysis. Furthermore, several machine learning models were developed based on the analysed behavioural outcomes of the interviewee to identify big five personality traits with Random Forest model yielding highest accuracy rate of over 75%. Our findings indicate that nonverbal behavioural cues can be utilized to determine personality traits.
Open Access
Air Pollution Mapping with Sensorbased Methodology
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Egodagama, W.G.C.N.; Zahid, A.A.M.; Pathirana, G.P.T.S.; Dissanayaka, D.S.; Chathurika, B.; Supunya, R.
the purpose of this study is to develop a sensor-based methodology(S-BM) for mapping air pollution (AP) related to Gaseous Composition of the Atmosphere in a specific area. It uses a drone equipped with sensors to identify the current composition of the air. After self-identifying the locations with specific distances in a specific area, the drone can go to those locations automatically and obtain sensor readings related to the gas percentages at those locations. After that the data is then transmitted to a computer program which analyzes (cluster analysis methodology), the data and then maps the air pollution in that specific area. Our results provide important informa-tion on how to measure, manage and atmospheric pollution mapping (APM). It also helps to identify airpolluted areas that need to be addressed quickly, and, thereby, it helps to save the atmosphere. We hope to program to get the sensor reading sand analyze the data with a suitable methodology and predict the condition of the atmosphere in the specific area. We hope to use cluster analysis and other analysis methodologies and technologies to this function. We need a dataset to train the model that can do the air quality prediction (AQP) of the relevant area. For that, we surfed the internet and found some datasets regarding the air pollution level of some major countries and their capitals. We think we will be able to make the model by using these datasets and predict the air pollution level of a specific area clearly. In addition, we are going to predict the future AP levels in a specific area by analyzing the current gas percentages of some specific gas components in the atmosphere like CO, CO2, SO2 and NH3 etc.
Embargo
An alternative approach for developing socially assistive robots
(IEEE, 2014-08-12) Sarrafzadeh, A; Jayawardena, C
This paper presents the design of the socially as-sistive companion robotic wheelchair named RoboChair. Unlike in most current companion robotics projects, the approach of RoboChair is not to build a completely new robotic device. Instead, the focus of the RoboChair project is to convert an already useful device (i.e. wheelchair) to a socially assistive companion robot. The authors argue that there are number of advantages in this approach. The proposed robotic chair is a mobile robot that can carry a person. It is equipped with several measuring devices for measuring vital signs. The robot chair is capable of engaging users with interactive dialogs through a touch screen and by using human-robot interaction techniques. It has a scalable modular software architecture so that adding new hardware and software modules is straightforward. The software framework is based on Robot Operating System (ROS) open source robotic middleware.
Embargo
Amazon Biology: An Augmented Reality-Based E-Book for Biology
(2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Somakeerthi, D.C.S.; De Silva, G. W. I.U.; De Silva, L.D.T.; Chandrasiri, S.; Joseph, J.K.
Biology is a conventionally struggling subject to learn from both high school and college students due to its complexity. Students are used to learning Biology from various methods such as reading textbooks, attending lectures. Biology is based on more practical and most of the schools not available proper lab facilities, anatomic structures, and resources to learn the module easily. And teachers who teach the module face a considerable number of issues when delivering the concepts. Some of them face unavailability of teaching aids, time-consuming, lack of lecture materials. Apart from that, the nature of the topic and the teaching style are the main learning problems faced by the students. Therefore, students do not learn the concepts perfectly and interest in the module has been reduced day by day. To overcome these difficulties “Amazon Biology,” mobile application has been proposed. The application consists of three major modules including image processing for the plant classification, augmented reality for human anatomy, and gamification. The proposed application has used the techniques in augmented reality and game-based learning. The developed system delivers nearly 85% level of accuracy and provides more advantages for students. They are effective and efficient learning, teaching via visual materials, and practical.
Embargo
Amazon Biology: An Augmented Reality-Based E-Book for Biology
(IEEE, 2020-12-10) Somakeerthi, D. C. S; De Silva, G. W. I. U; De Silva, L. D. T; Chandrasiri, S; Joseph, J. K
Biology is a conventionally struggling subject to learn from both high school and college students due to its complexity. Students are used to learning Biology from various methods such as reading textbooks, attending lectures. Biology is based on more practical and most of the schools not available proper lab facilities, anatomic structures, and resources to learn the module easily. And teachers who teach the module face a considerable number of issues when delivering the concepts. Some of them face unavailability of teaching aids, time-consuming, lack of lecture materials. Apart from that, the nature of the topic and the teaching style are the main learning problems faced by the students. Therefore, students do not learn the concepts perfectly and interest in the module has been reduced day by day. To overcome these difficulties “Amazon Biology,” mobile application has been proposed. The application consists of three major modules including image processing for the plant classification, augmented reality for human anatomy, and gamification. The proposed application has used the techniques in augmented reality and game-based learning. The developed system delivers nearly 85% level of accuracy and provides more advantages for students. They are effective and efficient learning, teaching via visual materials, and practical.
Embargo
Analysis and performance of CMA blind deconvolution for image restoration
(Wiley Online Library, 2015-09) Samarasinghe, P; Kennedy, R. A
In this paper we study the applicability of classical blind deconvolution methods such as constant modulus algorithm (CMA) for blind adaptive image restoration. The requirements such as the source to be white, uniformly distributed and zero mean, which yield satisfactory convergence in the data communication application context, are revisited in the image restoration context, where a linear deblur kernel needs to be blindly adapted to compensate for an unknown image blur kernel with the objective to recover a source ground truth image. Through analysis and performance studies, we show that the performance of CMA is adversely affected by the intrinsic spatial correlation of natural images and by any deviation of their distribution from being platykurtic. We also show that decorrelation techniques designed to overcome spatial correlation cannot be effectively applied to rectify CMA performance for blind adaptive image restoration
Embargo
Analysis of Cyber-Attack in Big Data IoT and Cyber-Physical Systems-A Technical Approach to Cybersecurity Modeling
(IEEE, 2019-03-29) Sen, S; Jayawardena, C
The Internet of Things (IoT) and Cyber-Physical Systems (CPS) are generating widespread data. Their success depends on a well secured infrastructure, which necessitates providing a robust infrastructure by securing the CPS and IoT system setup against the possibility of cyberattacks. With an increased utilization of CPS as well as widespread implementation of IoT with low power wireless sensors, the security vulnerability is growing, and increasing the possibility of cyberattacks. This paper has discussed models of how different categories of CPS can be stabilized in the event of a disaster, and analyzed how possible cyberattacks can be mitigated by taking a technical approach to model the cybersecurity.