Browsing by Author "Sudantha, BH"

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2nd International Conference on Information Technology Research 2017 (Pre Text)
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2017-12) Sudantha, BH
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4onse – 4 times open and non-conventional technology for sensing the environment: an integrated low-cost environmental monitoring system (ems) for developing countries
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2017-12) Ratnayake, GR; Mahanama, PKS; Warusavitharana, EJ; Weerasinghe, SN; Warnakulasooriya, KMHK; Sudantha, BH; Jayasuriya, YP; Sudantha, BH
4 times Open & Non-conventional technologies for Sensing the Environment (4ONSE) is an ongoing joint research project between University of Moratuwa, Sri Lanka and University of Applied Sciences and Arts of Southern Switzerland. This project was initiated in a time where the necessity of a low-cost, non-conventional, and precise hydrometeorological monitoring system has been of great demand due to the increased number of weather-related environmental hazards and disasters in Sri Lanka. This work comprises an integrated approach to setting-up an experimental nonconventional Environment Monitoring System (EMS) based on open hardware, open software, open standards and open data which could measure the rainfall, wind speed, wind direction, relative humidity, air temperature, barometric pressure, soil moisture, light intensity, and the water level. With comparison to other available weather stations, this research argues the cost effectiveness of the 4ONSE system, in terms of its technology, hardware and software. Such a fully accessible, royalty-free and low cost system could provide developing countries with accessible technology for the so called ‘Internet of Things’ economy. Even though the use of technologically sound and low system is necessary to monitor the environmental data, less is known about use, validity, accuracy and cost effectiveness of such systems. This research explores the accuracy of 4ONSE’s measurements against those of a reference station and further explores and proves its effectiveness and suitability in terms of environmental monitoring in the context of developing countries.
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4onse as a complementary to conventional weather observation network
(2019-12) Sudantha, BH; Warusavitharana, EJ; Ratnayake, GR; Mahanama, PKS; Warusavitharana, RJ; Tasheema, RP; Cannata, M; Strigaro, D; Sudantha, BH
Over the centuries, sensing the weather has been important to mankind for decision making. Weather observations are important to better understand the climate variability and its consequences which ranges over different temporal and spatial scales such as localized rainfall and thunderstorms to large scale storms and droughts. Analysis of climate induced phenomenon is data intensive and the data collected from very sparse network of professional weather stations have become incapable to forecast magnitude of the climate induced events. In this research, we present a 4ONSE network as a complementary to professional, state-owned weather station network. This open network was built on 4 open pillars – open hardware, open software, open standards and open data. Credibility of the network was assessed by analyzing the reliability and accuracy of data, cost incurred in building the station and conformity of measured parameters with WMO standards. Even though the 4ONSE station is not a high tech, professional weather station, these mini stations can be used to filling the gaps left by professional weather stations. Thus, they can be used to improve the coverage of the existing weather network of the country and to obtain the observations at near real time for producing accurate weather and disaster forecasts.
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An ad-hoc network based on low cost wi-fi device for iot device communication
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2017-12) Elvitigala, CS; Sudantha, BH; Sudantha, BH
This paper provides an implementation which solves some of the problems in establishing and operation of ad Hoc networks for embedded system based IoT devices. For the implementation of the system, it used the currently famous module of ESP8266 ESP07 version and the module provides all the necessary features and facilities expected to be in such framework. The system also can work independently and it provides most of the operations that is not available in the current systems. This paper also shows one of the applications tested in this research as an implementation of the system. This solves most of the communication issues faced in ad hoc networks of various embedded systems.
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Approach for general lossless visible watermarking
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2017-12) Mahenthirarasa, T; Ranathunga, L; Amalraj, CRJ; Sudantha, BH
the impact of the Internet has influenced in many new circumstances for the creation and delivery of content in digital form. An important issue that arises in these applications is the protection of the rights of all participants. It has been recognized for quite some time that current copyright laws are inadequate for dealing with digital image. This has led to an interest towards developing new copy deterrence and protection mechanisms. One such effort that has been attracting increasing interest is based on digital image watermarking techniques. Digital image watermarking is the process of embedding information into digital image content such that the information can later be extracted or detected for a variety of purposes including copy right protection and control. A visible watermark typically consists of a conspicuously visible message or a company logo indicating the ownership of the image. The system is designed for choosing best watermark for the cover image and three new algorithms for the visible watermarking process. Comparing and testing the three proposed algorithms is done in the evaluation process and highlight the best things of the algorithms proposed by using PSNR values.
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Automated student’s attendance entering system by eliminating forge signatures
Weerasinghe, KPMLP; Sudantha, BH
Entering student’s attendance into the excel sheets for each of the subjects, is very difficult, time consuming process. At the beginning of some course modules, the number of registered students are unknown. Lecturers use papers to take students attendance, so that the entering of student’s attendance is more complex. Automated student’s attendance entering system can be used to simplify the task. To build up such a system signature recognition and verification is important. The signature of a person is an important biometric attribute of a human being which can be used to authenticate human identity. To automate the process, this thesis consists of 3 phases.Signature identification and extraction from the attendance sheets and classification for testing process, Signature recognition by comparing each signature in the database and recognize the owner of the signature and the last phase is signature verification to identify whether the signature is original or counterfeit. In each phase, necessary image processing techniques are applied and useful features are extracted from each signature. Support Vector Machine (SVM) is used for classification of signatures extracted from attendance sheets. For signature recognition,multiclass Support Vector Machine is used and analyze using Fault Acceptance Ratio (FAR) and Fault Rejection Ratio (FRR) to check the accuracy of the classifier. Signature database consists only genuine signatures of each signer so that in signature verification stage a machine learning technique, Kolmogorov Smirnov test is used to verify the signature is belong to the original and if it is not match with the particular student’s signature, taken as zero. In this paper, off-line signature recognition & verification is proposed, where the signature is captured and presented to the user in an image format. A software package, Matlab2016b is used for this procedure. The described method in this thesis represents an effective and accurate approach to automatic signature recognition and verification. It is capable of matching the test signatures with the database of 83.33% accuracy. It is capable of classifying all signatures in the attendance sheet of 100% accuracy. In this work, it verifies 100% of signatures is original.Eventually, based on the methodologies employed in this thesis, it provides a promising stage for the development of an automated online signature detection system.
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Automatic classification of neonatal sleep-wake states based on facial video analysis
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2019-12) Mukai, Y; Morita, K; Shirai, NC; Wakabayashi, T; Shinkoda, H; Matsumoto, A; Noguchi, Y; Shiramizu, M; Sudantha, BH
Premature babies are admitted to the NICU (Neonatal Intensive Care Unit) for several weeks and generally placed under high medical supervision. To provide a better environment to them, some researchers investigate the affection of light and noise in the NICU on the formation of the sleep-wake cycle of the newborn called Circadian rhythm. These researches require the optimal evaluation method of the sleep-wake state. The visual assessment by nurses do not guarantee enough inter-tester reliability, and the measurement puts an additional burden on them. The conventional sleep-wake states discrimination method requires attachment devices on the subject's body. This paper proposes the automatic classification method of the sleep-wake states of neonates by using only facial information. In this research, we extract gradient features and spatio-temporal HOGV features from 3,600 face image frames (1 minute). According to Blazelton's method, this study classifies the sleep-wake states into six classes by using machine learning techniques. Support Vector Machine and Random Forest were used in the experiment. The spatio-temporal HOGV feature is an extension of the HOG feature to the time domain. The experiments using two kinds of feature quantities and classifiers showed that the highest accuracy rate (54.4%) was obtained by the gradient feature and Random Forest. This result suggested the possibility of improving accuracy by combining facial information with body movement and other conventional features.
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Blockchain & machine learning based secure personal medical record storage and sharing platform - datablock
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2019-12) Sharmilan, S; Farook, C; Sudantha, BH
Data is the most important part of machine learning. In the bioinformatics field, the sensitivity of the data is high and due to that, the accessibility of the data for a secondary purpose (e.g.: research) consists of many legal and ethical issues. Due to that in many bioinformatics research collecting the data consume more time than the development phase. There are some researches done to solve the legal and ethical issues by anonymizing the data using encryption, de-identification and perturbation of potentially identifiable attributes. But for some extend those solutions restricted the data breach but on the other hand, anonymized data not performed well during the analysis and mining tasks and some researches done to generate fake data like the real data sets. But those researches not full fill the requirements because of the generated data more restricted to the knowledge of the training data. The evolution of Blockchain provided a secure and trusted way to transfer valuable assets between two unknown parties. This research used Blockchain technology to store and share personal medical data to data scientists. And that will help them to build more accurate and efficient models. It also proposed a machine learning model to predict the authenticity and validity of the personal data based on domain knowledge and the validator's trust percentage.
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Blockchain based decentralized knowledge sharing system - jigsaw
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2019-12) Azeem, A; Jajeththanan, S; Sharmilan, S; Sudantha, BH
Knowledge is formalized information that is cited or used in logical inference. The growth of knowledge sharing in the field of education helps people understand and grow their potential. Individuals are willing to share knowledge when they are certain to benefit from reciprocity or build a reputation. Individuals spend enormous amounts of time, resources and scarifications to gain knowledge. Individuals are currently sharing their expertise through forums, vlogs, videos, and trainings. Nevertheless, there is a variety of untrusted and unvalidated knowledge available for a subject from the recipient's point of view. To grasp what they need, it requires multiple resources. There are no direct benefits for people who make, comment or vote for these resources. In this research, the researcher implemented a distributed knowledge sharing system centered on Blockchain to allow multiple individuals to contribute their knowledge by building a resource that is moderated, verified, and community structured. Each creator, commenter and voter of knowledge will receive rewards, and the knowledge invested will gain it forever. The researchers used cryptography and knowledge economy in addition to stellar blockchain to make this process secure and more trustable. In this paper, the proposed system is realistic, efficient and has an ever-earning model.
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Building an open-source environmental monitoring system - a review of state-of-the-art and directions for future research
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2018) Sudantha, BH; Warusavitharana, EJ; Ratnayake, GR; Mahanama, PKS; Cannata, M; Strigaro, D; Wijesiriwardana, CP
The massive development take place in the field of IoT (Internet of Things) has enabled generation of large set of real time environmental data from low cost sensor networks. This has enabled developing nations to monitor their environments with more economical options. The environmental monitoring network of Sri Lanka is mainly handled by the government bodies such as Meteorological Department, Irrigation Department and Central Environmental Authority. Most of the systems are manually operated and sparsely distributed. The automated systems are restricted to certain main cities of the country. Thus, the data provided by the existing network not capable enough to generate reliable climate or disaster specific forecasts. The available data is mostly retained as hard copies and they are not freely and publicly available. Hence, every time, the researchers and decision makers need to purchase data and required to undergo redundant data collection procedures. In this context, the 4ONSE research project on developing an experimental, open-source, low cost and non-conventional Environmental Monitoring System (EMS) can be considered as the 1st initiative in Sri Lanka which creates a new revolution in the country for environmental data viewing and sharing without any charge. 4ONSE is the acronym for 4 times Open and Non-Conventional technology for Sensing the Environment, which is a joint research between University of Moratuwa and University of Applied Sciences and Arts of Southern Switzerland (SUPSI). Deduru Oya river basin area is the selected study area to deploy the 4ONSE systems. The Deduru Oya is 115km long and covers 2687km2 of catchment area. It carries flash floods during rainy seasons and very low flow during the dry seasons. Hence, the selected case study area is ideal for developing any forecasting application based on the real time environmental data. The project team has already deployed 27 systems in the basin. Temperature, rainfall, atmospheric pressure, solar radiation, relative humidity, soil moisture, wind speed and direction are the parameters measured by the system. In this research we attempt to present the state of the art of open source based environmental monitoring, architecture of the 4ONSE system, motivations behind deployment of the 4ONSE system and finally the lessons for the future research and development.
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Change detection and tracking using synthetic aperture radar videos
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2019-12) Maithree, H; Dinushka, D; Wijayasiri, A; Sudantha, BH
In this paper, a change detection technique which can be utilized in identifying important changes in SAR videos has been proposed. Even though most researches have done on change detection in multi temporal SAR images, implementing a methodology to identify changes in SAR videos in a near real time manner has unique challenges such as the inherent speckle noise which will increase the false positive rate of the detection, rotation of the reconstructed SAR video frames due to the movement of the airborne vehicle, dynamic background and the overlapping of the area in consecutive video frames, non-uniform backscattering of SAR pulses and shadowy modelling of objects in video frames which doesn't provide much information about the appearance model of the objects. We propose an algorithm based on combination of optical flow calculation using Lucas Kanade method(LK method) and blob detection to detect the changes, and we feed the detected changes along with optical flow calculations to a centroid tracking algorithm to track the detected changes throughout the video.
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A color mask and trained image set for the creation of new technique for indoor robotic navigation
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2018) Warnakulasooriya, KMHK; Sudantha, BH; Premachandra, C; Wijesiriwardana, CP
Among the different methods used in the indoor navigation of robotic systems image processing techniques are widely used. This research was focused to explore a new dimension of image capturing and matching in order to enhance the indoor navigation methods of moving robots. The color extraction were carried out by performing the logical operation between a color mask and the original image. The color mask would be created considering the bitwise range analysis. The real comparison has been received analyzing the histograms received from color extraction and the trained source image.
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Conversational agent acting as a shopping assistant for e-commerce sites
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2017-12) Walgama, MS; Sirisuriya, SCM de S; Sudantha, BH
E-commerce has been gaining momentum drastically over past few years with new trends in technology. The key entity of any e-commerce business is to provide the customer with maximum benefits. Due to this reason using sophisticated technology in ecommerce aspects were seen vividly. With the rapid improvement and usage of messaging apps 2015 most of the business entities where interested in shifting their business deals through most of the messaging apps. The concept of messaging apps where further developed in to a phase of using an embedded conversational interface which allows the customer and the business to deal peacefully. E commerce sites provide a key word search along with a menu driven navigation. Users have come across issues in choosing the exact item needed with the prevailing system. It is reported that about 80% of web shoppers have left the e-commerce sites due to not finding what they needed. To address this problem, the concept of Natural Language interface acting as a shopping assistant was developed. This will build a conversation with the user forwarding a series of questions regarding the goods the user wishes to purchase. This system is mainly developed using AIML scripting, java and prolog.
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Detecting and capturing the intensity of a brain tumor using mri images
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2019-12) Gayanga, TDL; Pathirana, GPSN; Sandanayake, TC; Sudantha, BH
Mutated cells in the brain are known as tumors. There are two types of tumors present in the brain, and they are malignant and benign tumors. Benign tumors are non-cancerous tumors which reside inside a person's brain having a primitive shape and size. Malignant tumors are cancerous brain tumors which spread by transforming the cells into the cell type next to the malignant tumor and have no clearly defined edge or shape(cloudy). Treatment planning and detection is the most efficient way of treating a patient and improving the condition. Magnetic Resonance Imaging (MRI) is the established method to detect the tumors. After the detection classification of the tumor manually takes reasonable time and sometimes it is impossible to detect the type with the naked eye. This results in having to conduct a biopsy which is a risk as well as sometimes impossible. One of the main factors to be considered in segmenting the tumor is the edge intensity of the tumor. For detecting the intensity of the tumor edge a novel completely automatic and reliable detection based on CNN is proposed. Pre-processing and running the improved images through CNN to get the best possible features to be extracted from the MRI images. Canny edge detection and Wavelet transform are applied to detect the edge and finally, Hough transform is used to detect the intensity of the edge. Edge detection method that proposed in this paper will have a wide verity of surgical applications.
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Detecting automatically generated tweets using lexical analysis and profile credibility
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2019-12) Wickramarathna, NC; Ganegoda, GU; Sudantha, BH
Every industry relies heavily on accurate news and information distribution. In the recent decade social media has become one of the main methods of sharing news and other social impacting information online. But there's an uprising threat to all social media platforms, especially for twitter, known as bots. Not all bots are malicious but these automated accounts are largely responsible for platform manipulation, which is the process of misleading, disrupting the experience of other users by engaging in deceptive, aggressive activities. There are many politically motivated groups in Facebook and Twitter who use various levels of manipulation to influence voters and thereby undermining the democratic process. Platform manipulation is not only carried out by malicious automation, but also with spam and inauthentic accounts (fake accounts). This paper presents novel methodology to detect these bots (automated accounts) using existing research as foundation and builds new research solution to the problem. This methodology can be applied to the news domain to find bots involved in spreading false information. This methodology classifies a given tweet into either fake news or not and use the result as a feature and in addition to that user credibility can also be taken into account.
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Feasibility evaluation of a solar powered automobile air-conditioning system
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2019-12) Ranaweera, WMMS; Nadhira, KF; Rathnayake, RPL; Alahakoon, PMK; Kumara, WGCW; Sudantha, BH
The rising demand for energy growth worldwide is a major crisis in the present. Development of the renewable energy creates new efficient solutions to existing applications. Currently, solar power is the best renewable energy source. Air-conditioning provides comfort living in sub-tropical countries like Sri Lanka. Solar-powered air-conditioning will reduce the operating costs. Therefore, this paper focuses on design and construction of a solar-powered air-conditioner for automobiles. Implementation of the solar powered air-conditioner in an automobile, will increase the fuel efficiency while reducing the carbon emissions. Further, by isolating the compressor from the engine and powering through the solar energy, engine load decreases. Experimental calculations are presented considering a 35 seater bus.
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Feature based speaker embedding on conversational speeches
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2019-12) Balasubramaniyam, H; Amalraj, CRJ; Sudantha, BH
Identifying the speaker of a specific speech by examining the speech features of the voice is called speaker identification. The task of speaker identification consists of three main phases which are feature extraction, feature embedding and voice classification. Speaker embedding is the process of modeling the voice of a person where the model of the utterance can uniquely represent the speaker of that voice. Speaker embedding is a commonly used method in Automatic Speaker Recognition systems to identify the voice of the speaker. Currently, Deep Neural Networks based approaches are used in these systems for speech feature extraction and speech embedding. The performances of different approaches heavily depend on the noise factor and suitability of selected features of the audio data. MFCC, LPC, Dimensional filter banks are some of the frequently used speech features in speaker recognition. This speaker recognition research focuses on the usage of speech features for speaker embedding that are fitting for the speaker identification in conversational environment using a Convolutional Neural Network based approach.
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Generate bioinformatics data using generative adversaria l network: a review
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2017-12) Sharmilan, S; Chaminda, HT; Sudantha, BH
Data is the most important part in machine learning. In bioinformatics field the sensitivity of the data is high and due to that the accessibility of the data for a secondary purpose (e.g.: research) is consist with many legal and ethical issues. Due to that in many bioinformatics researches collecting the data consume more time than the development phase. There are some researches done to solve the legal and ethical issues by anonymising the data using encryption, de-identification and perturbation of potentially identifiable attributes. For some extend those solutions restricted the data breach but in other hand anonymized data not performed well during the analysis and mining tasks. Recently Generative adversarial networks (GANs) have become a research focus of artificial intelligence. The goal of GANs is to estimate the potential distribution of real data samples and generate new samples from that distribution. Here, researcher review GAN in bioinformatics to generate data sets, presenting examples of current research. To provide a useful and comprehensive perspective, Researcher categorize research both by the bioinformatics data and GAN architecture and flow. Additionally, discussed about the issues of GAN in bioinformatics to generate data sets and suggest future research directions. Researcher believes that this review will provide valuable insights for researchers to apply GAN to generate bioinformatics data sets.
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Gis powered an automated generic flood model for river basins in Sri Lanka
(Faculty of Information Technology, University of Moratuwa., 2021-12) Bandara, MNL; Premasiri, HMR; Sudantha, BH; Ganegoda, GU; Mahadewa, KT
Flood is the most common and deadliest form of disaster that affects lives and properties all around the world. Predicting natural disasters is very complex due to the lack of proper methods and resources in countries like Sri Lanka. But if there is an efficient prediction system it helps to save not only lives but the environment and infrastructure too. Therefore, the aim of this study is to pave the pathway to build an efficient and effective flood prediction system through analysing available flood modelling techniques and their applications to find their strengths and weaknesses. Then the result of the study could be used to put the foundation for the main requirement of building the system to predict natural disasters. A generic model was developed to take any DEM data and a pour point feature class layer for the specific DEM to generate outputs based on other variables that could be input to the model. It gave model calibration capability as well as significant time saving on tasks. The use of special tools like the ‘Parse Path’ tool in ArcGIS Pro, gave the capability to name output easily and quickly. And it also made saving so efficient because it automatically saves all the results to the file path of the DEM. Due to these factors, when it starts raining in the upper catchment area, could forecast due inundation area in minutes. Including the GIS technology could improve the data quality and availability while incorporating different data sources for more in-depth analysis could give more accurate predictions. Using the GIS-based hydrological model, a suitable system to implement in Sri Lanka could be developed.
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Gps-android based location tracking system for public transportation (trackit)
Vithanage, RR; Sudantha, BH
Public transportation has been considered as the main mode of transportation in Sri Lanka. General public can view static time table of public transportation but properly aligning the transportation with the correct time table is not happening due to various reasons such as traffic conditions, bad road condition and some technical or human resource unavailability. From the passenger’s perspective, they do not have a method to find the actual location or availability of the bus or train causing to waste of time waiting on bus shelters and railway stations. Therefore some method for location tracking for transportation system is important to enable passengers to reduce their time wastage. Many researches have been conducted on location tracking and monitoring in the world. With the spreading of information technology, over the past few years there have been some attempts to enhance the quality of public transportation with the application of information and communication technology. However still there is no proper mechanism to find real time location of a bus or train although there are some commercial tracking systems to track private vehicles by installing some costly hardware devices. This research focused on utilizing commonly used technologies and infrastructure to implement the location tracking system for public transportation sector. The system consisting of a web application and a mobile application to enable location tracking. The web application is the core of the system which provides the interface for the general public to view the schedules and actual location of the bus or train. In addition to the location information, it predicts time of arrival/destination through analyzing previous data and current live data. The administration panel of the main web application enable management of all master data of the system. With this system, it is expected to facilitate passengers to make better travelling decisions by providing required information for them. Also relevant authorities also can use system data to support decisions to enhance railway service and bus services. During the evaluation, it was shown that system was successful more than 70%.