Browsing by Author "Wijayasiri, A"

Now showing 1 - 8 of 8

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Blockchain-based software subscription and licenses management system
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa., 2023-12-07) De Alwis, H; Wijayasiri, A; De Silva, S; De Silva, K; Piyatilake, ITS; Thalagala, PD; Ganegoda, GU; Thanuja, ALARR; Dharmarathna, P
Current software licensing models exhibit shortcomings in transparency, security, and adaptability. Addressing these challenges, this study presents a novel blockchain-based licensing system using the Ethereum platform. By employing smart contracts and the ERC721 and ERC20 token standards, the system ensures automated, transparent, and secure license agreement enforcement and facilitates license token operations. Influenced by the rise of subscription licenses and the implications of the UsedSoft court decision, the research designs a blockchain-driven subscription license model, analyses the UsedSoft case’s impact on license transfers, and formulates specialized smart contracts for varied licensing models. The approach signifies a marked advancement in contemporary software licensing practices.
item: Conference-Full-text
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.
item: Conference-Abstract
Crime analytics : analysis of crimes through newspaper articles
Jayaweera, I; Sajeewa, C; Liyanage, S; Wijewardane, T; Perera, GIUS; Wijayasiri, A
Crime analysis is one of the most important activities of the majority of the intelligent and law enforcement organizations all over the world. Generally they collect domestic and foreign crime related data (intelligence) to prevent future attacks and utilize a limited number of law enforcement resources in an optimum manner. A major challenge faced by most of the law enforcement and intelligence organizations is efficiently and accurately analyzing the growing volumes of crime related data. The vast geographical diversity and the complexity of crime patterns have made the analyzing and recording of crime data more difficult. Data mining is a powerful tool that can be used effectively for analyzing large databases and deriving important analytical results. This paper presents an intelligent crime analysis system which is designed to overcome the above mentioned problems. The proposed system is a web-based system which comprises of crime analysis techniques such as hotspot detection, crime comparison and crime pattern visualization. The proposed system consists of a rich and simplified environment that can be used effectively for processes of crime analysis.
item: Conference-Full-text
Crime Analytics: Analysis of Crimes Through Newspaper Articles
(2015-08-03) Jayaweera, I; Sajeewa, C; Liyanage, S; Wijewardane, T; Perera, I; Wijayasiri, A
Crime analysis is one of the most important activities of the majority of the intelligent and law enforcement organizations all over the world. Generally they collect domestic and foreign crime related data (intelligence) to prevent future attacks and utilize a limited number of law enforcement resources in an optimum manner. A major challenge faced by most of the law enforcement and intelligence organizations is efficiently and accurately analyzing the growing volumes of crime related data. The vast geographical diversity and the complexity of crime patterns have made the analyzing and recording of crime data more difficult. Data mining is a powerful tool that can be used effectively for analyzing large databases and deriving important analytical results. This paper presents an intelligent crime analysis system which is designed to overcome the above mentioned problems. The proposed system is a web-based system which comprises of crime analysis techniques such as hotspot detection, crime comparison and crime pattern visualization. The proposed system consists of a rich and simplified environment that can be used effectively for processes of crime analysis.
item: Conference-Full-text
Exploring state-of-the-art research on blockchain adoption in the construction industry: a systematic literature review
(Ceylon Institute of Builders - Sri Lanka, 2023-07-21) Hirusheekesan, S; Kulatunga, U; Wijayasiri, A
Blockchain is often considered a potential disrupter in how industries operate, due to its decentralised nature and several other salient features like enhanced security, transparency, traceability, immutability etc. The Construction Industry, though regarded as a late adopter of technologies, is striving to harness blockchain to improve its processes. The subsequent research initiatives, however, are scattered around several application areas, with different levels of maturity. This would prove troublesome for a potential researcher to identify a suitable research gap and carry out impactful research. Addressing this, the study attempts to identify the evolution of blockchain research in the construction industry and its current and future trends through a systematic literature review. The review identified that blockchain research is gaining popularity in construction sector exponentially and is expected to continue that pace. The developed countries are dominating these application oriented researches while developing economies are lacking behind. Research on adopting blockchain in procurement and design and construction processes has been done substantially while newer topics are evolving since the beginning of this decade, focusing on the sustainability initiatives of the sector and fusing other digital technologies with blockchain. It is believed that while procurement and design related researches iterate their findings, these new topics would define the blockchain researches in the years to come. Also, attention should be paid on holistically evaluating the blockchain solutions considering not only the technological aspect but also the sustainability, resilience and the productivity of the industry, which is yet to be observed in the studies.
item: Conference-Full-text
Forevidizer forensic video & image analyzing toolkit
(2013) Wijayasiri, A; Sampath, C; Rathnayaka, N; Jayaweera, R; De Silva, C
Digital videos and images have become a common thing in life. More and more sophisticated tools are becoming available for the general consumers. With the advancement of digital image processing and video processing technologies, various kinds of images and videos are produced from different perspectives. As a result videos can be used for various frauds and illegal activities. Legislative changes have been made to accept videos and images from digital cameras as witnesses for legal proceedings. Consequently there is a growing interest in forensic analysis of video content where the integrity of digital images and videos need to be checked. In this respect it has become essential to have a proper toolkit to analyze whether a particular video is a real one or one that has been tampered with. As video editing techniques are getting very sophisticated, tampered videos are hard to detect. However, when a video is tampered with, some of the basic properties of the video are changed. Then to detect those changes it is needed to use complex image processing and video processing techniques and algorithms. We present methods to analyze these properties of a given video, and produce statistical details for the video to ascertain whether it is tampered with or not, and if it is tampered with then what changes have been made. Video frame duplicate detection, video double MPEG compression detection, image double JPEG compression detection and duplicated regions within image detection are the basic methods offorgery detections.
item: Conference-Full-text
Forevidizer: forensic video & image analyzing toolkit
(The Engineering Research Unit, University of Moratuwa, 2013-02) Wijayasiri, A; Sampath, C; Rathnayaka, N; Jayaweera, R; De Silva, C; Rodrigo, R
Digital videos and images have become a common thing in life. More and more sophisticated tools are becoming available for the general consumers. With the advancement of digital image processing and video processing technologies, various kinds of images and videos are produced from different perspectives. As a result videos can be used for various frauds and illegal activities. Legislative changes have been made to accept videos and images from digital cameras as witnesses for legal proceedings. Consequently there is a growing interest in forensic analysis of video content where the integrity of digital images and videos need to be checked. In this respect it has become essential to have a proper toolkit to analyze whether a particular video is a real one or one that has been tampered with. As video editing techniques are getting very sophisticated, tampered videos are hard to detect. However, when a video is tampered with, some of the basic properties of the video are changed. Then to detect those changes it is needed to use complex image processing and video processing techniques and algorithms. We present methods to analyze these properties of a given video, and produce statistical details for the video to ascertain whether it is tampered with or not, and if it is tampered with then what changes have been made. Video frame duplicate detection, video double MPEG compression detection, image double JPEG compression detection and duplicated regions within image detection are the basic methods of forgery detections.
item: Conference-Full-text
Short-Term Traffic Forecasting using LSTM-based Deep Learning Models
(2021-07) Haputhanthri, D; Wijayasiri, A; Adhikariwatte, W; Rathnayake, M; Hemachandra, K
Accurate short-term traffic volume forecasting has become a component with growing importance in traffic management in intelligent transportation systems (ITS). A significant amount of related works on short-term traffic forecasting has been proposed based on traditional learning approaches, and deep learning-based approaches have also made significant strides in recent years. In this paper, we explore several deep learning models that are based on long-short term memory (LSTM) networks to automatically extract inherent features of traffic volume data for forecasting. A simple LSTM model, LSTM encoder-decoder model, CNN-LSTM model and a Conv-LSTM model were designed and evaluated using a real-world traffic volume dataset for multiple prediction horizons. Finally, the experimental results are analyzed, and the Conv-LSTM model produced the best performance with a MAPE of 9.03% for the prediction horizon of 15 minutes. Also, the paper discusses the behavior of the models with the traffic volume anomalies due to the Covid-19 pandemic.